timeseries listlengths 3 3 | cols listlengths 3 3 | question stringlengths 775 987 | question_type stringclasses 3 values | answer stringlengths 30 113 | attributes listlengths 1 1 | ability_types listlengths 1 1 | options listlengths 4 4 | correct_index int64 0 3 |
|---|---|---|---|---|---|---|---|---|
[
[
-0.149731528124002,
-0.12079291987974101,
-1.683666407665344,
-1.683008712818919,
-0.19109585408211302,
-0.20897117288636002,
-0.157506464087231,
-1.4678716706544521,
-0.112806630566238,
-0.13582588893841302,
0.07120731821232701,
0.029584596822800003,
0.06113056... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration increases sharply while the temperature remains stable", "temperature climbs gradually with vibration tracking normal", "a single vibration spike precedes a sharp temperature rise", "vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline"] | what_happened | vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline | [
"vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline"
] | [
"MCQ_obs"
] | [
"vibration increases sharply while the temperature remains stable",
"temperature climbs gradually with vibration tracking normal",
"a single vibration spike precedes a sharp temperature rise",
"vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline"
] | 3 |
[
[
-0.149731528124002,
-0.12079291987974101,
-1.683666407665344,
-1.683008712818919,
-0.19109585408211302,
-0.20897117288636002,
-0.157506464087231,
-1.4678716706544521,
-0.112806630566238,
-0.13582588893841302,
0.07120731821232701,
0.029584596822800003,
0.06113056... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["slow alignment drift with increasing dynamics", "lubrication degradation with minimal dynamic variation", "operational pause followed by restart with typical conditioning", "severe gear wear with rapid progression"] | how_happened | slow alignment drift with increasing dynamics | [
"slow alignment drift with increasing dynamics"
] | [
"MCQ_cause"
] | [
"slow alignment drift with increasing dynamics",
"lubrication degradation with minimal dynamic variation",
"operational pause followed by restart with typical conditioning",
"severe gear wear with rapid progression"
] | 0 |
[
[
-0.149731528124002,
-0.12079291987974101,
-1.683666407665344,
-1.683008712818919,
-0.19109585408211302,
-0.20897117288636002,
-0.157506464087231,
-1.4678716706544521,
-0.112806630566238,
-0.13582588893841302,
0.07120731821232701,
0.029584596822800003,
0.06113056... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor for early signs of heat increase and schedule an inspection", "quickly check rollers for potential lock-up when loaded", "keep track of planned stop and restart occurrences", "monitor slow alignment drift and plan a precision alignment check"] | suggested_fix | monitor slow alignment drift and plan a precision alignment check | [
"monitor slow alignment drift and plan a precision alignment check"
] | [
"MCQ_fix"
] | [
"monitor for early signs of heat increase and schedule an inspection",
"quickly check rollers for potential lock-up when loaded",
"keep track of planned stop and restart occurrences",
"monitor slow alignment drift and plan a precision alignment check"
] | 3 |
[
[
0.013572218573245,
0.231911640064691,
1.3044281887006601,
-8.463294231518027,
-1.079597935541795,
-8.380384400083658,
0.18470309748652303,
0.6703596866504421,
1.599185950464673,
0.729960392516054,
0.17585145178682401,
0.442874572896276,
0.43992355535592503,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations", "vibration and temperature both show parallel gradual increases", "a sharp temperature increase appears while vibration stays within its normal range", "a rapid transition yields a different sustained vibration level"] | what_happened | vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations | [
"vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations"
] | [
"MCQ_obs"
] | [
"vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations",
"vibration and temperature both show parallel gradual increases",
"a sharp temperature increase appears while vibration stays within its normal range",
"a rapid transition yields a different sustained vibration leve... | 0 |
[
[
0.013572218573245,
0.231911640064691,
1.3044281887006601,
-8.463294231518027,
-1.079597935541795,
-8.380384400083658,
0.18470309748652303,
0.6703596866504421,
1.599185950464673,
0.729960392516054,
0.17585145178682401,
0.442874572896276,
0.43992355535592503,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["slow alignment drift with increasing dynamics", "foreign material collision that gets stuck and sustains persistent rubbing contact", "progressive deterioration of the gear system", "accelerated wear affecting gears significantly"] | how_happened | slow alignment drift with increasing dynamics | [
"slow alignment drift with increasing dynamics"
] | [
"MCQ_cause"
] | [
"slow alignment drift with increasing dynamics",
"foreign material collision that gets stuck and sustains persistent rubbing contact",
"progressive deterioration of the gear system",
"accelerated wear affecting gears significantly"
] | 0 |
[
[
0.013572218573245,
0.231911640064691,
1.3044281887006601,
-8.463294231518027,
-1.079597935541795,
-8.380384400083658,
0.18470309748652303,
0.6703596866504421,
1.599185950464673,
0.729960392516054,
0.17585145178682401,
0.442874572896276,
0.43992355535592503,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor slow alignment drift and plan a precision alignment check", "quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired", "monitor scheduled shutdown and restart activities", "immediately check for a sudden alignment change and ensure proper machine alignment"] | suggested_fix | monitor slow alignment drift and plan a precision alignment check | [
"monitor slow alignment drift and plan a precision alignment check"
] | [
"MCQ_fix"
] | [
"monitor slow alignment drift and plan a precision alignment check",
"quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired",
"monitor scheduled shutdown and restart activities",
"immediately check for a sudden alignment change and ensure proper machine alignment"
] | 0 |
[
[
0.663869392523967,
-0.47943436851102605,
-0.48571084009542004,
-0.467846637891255,
-0.11925468678067401,
-0.5827564293036961,
-0.632485883483871,
-0.7324288370163871,
-0.301275816082479,
-0.35438552864093403,
-0.22981958282488202,
-0.375629413664316,
-0.47122632... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration increases sharply while the temperature remains stable", "a coordinated abrupt increase is noted in both temperature and vibration", "vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations", "temperature shows a gradual rise while vibration remains within its normal band"] | what_happened | vibration increases sharply while the temperature remains stable | [
"vibration increases sharply while the temperature remains stable"
] | [
"MCQ_obs"
] | [
"vibration increases sharply while the temperature remains stable",
"a coordinated abrupt increase is noted in both temperature and vibration",
"vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations",
"temperature shows a gradual rise while vibration remains within its no... | 0 |
[
[
0.663869392523967,
-0.47943436851102605,
-0.48571084009542004,
-0.467846637891255,
-0.11925468678067401,
-0.5827564293036961,
-0.632485883483871,
-0.7324288370163871,
-0.301275816082479,
-0.35438552864093403,
-0.22981958282488202,
-0.375629413664316,
-0.47122632... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["gradual misalignment with rising dynamic conditions", "alterations in running condition due to belt splice rework", "an abrupt increase in friction on the rolling track with little dynamic alteration", "abrupt alignment shift with minimal thermal impact"] | how_happened | gradual misalignment with rising dynamic conditions | [
"gradual misalignment with rising dynamic conditions"
] | [
"MCQ_cause"
] | [
"gradual misalignment with rising dynamic conditions",
"alterations in running condition due to belt splice rework",
"an abrupt increase in friction on the rolling track with little dynamic alteration",
"abrupt alignment shift with minimal thermal impact"
] | 0 |
[
[
0.663869392523967,
-0.47943436851102605,
-0.48571084009542004,
-0.467846637891255,
-0.11925468678067401,
-0.5827564293036961,
-0.632485883483871,
-0.7324288370163871,
-0.301275816082479,
-0.35438552864093403,
-0.22981958282488202,
-0.375629413664316,
-0.47122632... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["immediately look for any severe structural looseness and secure or repair as needed", "record restart events alongside immediate load activation", "track progressive structural looseness and schedule inspection before progression", "stop machine operation immediately and substitute the bearing that shows an abrupt wear shift"] | suggested_fix | track progressive structural looseness and schedule inspection before progression | [
"track progressive structural looseness and schedule inspection before progression"
] | [
"MCQ_fix"
] | [
"immediately look for any severe structural looseness and secure or repair as needed",
"record restart events alongside immediate load activation",
"track progressive structural looseness and schedule inspection before progression",
"stop machine operation immediately and substitute the bearing that shows an ... | 2 |
[
[
0.685458001448892,
0.7328884569750751,
0.680857392756783,
0.690681912936793,
0.43100100396420105,
-2.606455882275177,
-2.6102550757531713,
0.409689822815401,
0.48941342069310007,
0.40428786525186206,
-2.640203422142528,
-2.600163464345476,
0.358548988975296,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature ascends gradually, with vibration staying within its usual range", "vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline", "vibration momentarily spikes and then settles while temperature stays steady", "temperature and vibration experience a sharp concurrent rise"] | what_happened | vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline | [
"vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline"
] | [
"MCQ_obs"
] | [
"temperature ascends gradually, with vibration staying within its usual range",
"vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline",
"vibration momentarily spikes and then settles while temperature stays steady",
"temperature and vibration experi... | 1 |
[
[
0.685458001448892,
0.7328884569750751,
0.680857392756783,
0.690681912936793,
0.43100100396420105,
-2.606455882275177,
-2.6102550757531713,
0.409689822815401,
0.48941342069310007,
0.40428786525186206,
-2.640203422142528,
-2.600163464345476,
0.358548988975296,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["incremental imbalance formation in mechanical systems", "severe gear wear with rapid progression", "initial contact shock followed by sustained belt rubbing against structure", "a sudden increase in friction along the rolling path with negligible dynamic variation"] | how_happened | incremental imbalance formation in mechanical systems | [
"incremental imbalance formation in mechanical systems"
] | [
"MCQ_cause"
] | [
"incremental imbalance formation in mechanical systems",
"severe gear wear with rapid progression",
"initial contact shock followed by sustained belt rubbing against structure",
"a sudden increase in friction along the rolling path with negligible dynamic variation"
] | 0 |
[
[
0.685458001448892,
0.7328884569750751,
0.680857392756783,
0.690681912936793,
0.43100100396420105,
-2.606455882275177,
-2.6102550757531713,
0.409689822815401,
0.48941342069310007,
0.40428786525186206,
-2.640203422142528,
-2.600163464345476,
0.358548988975296,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["check immediately the roller showing severe heating and replace if damaged", "immediately resolve product blockage and assess conveyor pathway", "maintain observation of incremental imbalance formation and arrange for balancing service", "examine for any object that could have struck and become lodged, then clear the conveyor route to stop friction"] | suggested_fix | maintain observation of incremental imbalance formation and arrange for balancing service | [
"maintain observation of incremental imbalance formation and arrange for balancing service"
] | [
"MCQ_fix"
] | [
"check immediately the roller showing severe heating and replace if damaged",
"immediately resolve product blockage and assess conveyor pathway",
"maintain observation of incremental imbalance formation and arrange for balancing service",
"examine for any object that could have struck and become lodged, then ... | 2 |
[
[
-2.143109755667122,
-0.15852932335633202,
-0.24721260595263103,
-0.14921648428004902,
-0.08868328259629901,
-2.144802994476365,
-2.143109755667122,
-2.143109755667122,
-2.1340086024882092,
-2.147660334227768,
-0.0947154337807,
-0.05492430402279701,
0.00476239061... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 162 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a rapid temperature rise is noted while vibration remains stable at its baseline", "vibration momentarily spikes and then settles while temperature stays steady", "temperature trends upward at a gradual pace as vibration remains within acceptable levels", "vibration steadily ascends over time, and temperature maintains a baseline pattern"] | what_happened | vibration steadily ascends over time, and temperature maintains a baseline pattern | [
"vibration steadily ascends over time, and temperature maintains a baseline pattern"
] | [
"MCQ_obs"
] | [
"a rapid temperature rise is noted while vibration remains stable at its baseline",
"vibration momentarily spikes and then settles while temperature stays steady",
"temperature trends upward at a gradual pace as vibration remains within acceptable levels",
"vibration steadily ascends over time, and temperatur... | 3 |
[
[
-2.143109755667122,
-0.15852932335633202,
-0.24721260595263103,
-0.14921648428004902,
-0.08868328259629901,
-2.144802994476365,
-2.143109755667122,
-2.143109755667122,
-2.1340086024882092,
-2.147660334227768,
-0.0947154337807,
-0.05492430402279701,
0.00476239061... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 162 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["sudden belt strike against structure causing immediate friction spike and dynamic shock", "sudden product jam creating immediate shock impact and friction surge", "slow wearing-related deterioration in bearing and gear", "ongoing imbalance emergence within mechanical components"] | how_happened | ongoing imbalance emergence within mechanical components | [
"ongoing imbalance emergence within mechanical components"
] | [
"MCQ_cause"
] | [
"sudden belt strike against structure causing immediate friction spike and dynamic shock",
"sudden product jam creating immediate shock impact and friction surge",
"slow wearing-related deterioration in bearing and gear",
"ongoing imbalance emergence within mechanical components"
] | 3 |
[
[
-2.143109755667122,
-0.15852932335633202,
-0.24721260595263103,
-0.14921648428004902,
-0.08868328259629901,
-2.144802994476365,
-2.143109755667122,
-2.143109755667122,
-2.1340086024882092,
-2.147660334227768,
-0.0947154337807,
-0.05492430402279701,
0.00476239061... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 162 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["ensure that the belt has been replaced or reset properly", "track the slow progression of wear-related issues and set up an inspection", "ensure continuous monitoring of slow imbalance changes and set up balancing maintenance", "immediately resolve product blockage and assess conveyor pathway"] | suggested_fix | ensure continuous monitoring of slow imbalance changes and set up balancing maintenance | [
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance"
] | [
"MCQ_fix"
] | [
"ensure that the belt has been replaced or reset properly",
"track the slow progression of wear-related issues and set up an inspection",
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance",
"immediately resolve product blockage and assess conveyor pathway"
] | 2 |
[
[
-0.17309006434512703,
-0.021093238596697,
-0.20077046026515602,
-0.418885129979283,
-2.5225602108524052,
-0.46513590963925705,
-0.5691650778132771,
-0.515346067736007,
-0.460791085761784,
-0.42918639746590104,
-0.072775006334392,
-0.433986671829434,
-0.539242181... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration trends upward gradually as temperature exhibits baseline fluctuations", "a sharp temperature increase appears while vibration stays within its normal range", "temperature and vibration show a coordinated, slow increase", "temperature shows a gradual rise while vibration remains within its normal band"] | what_happened | vibration trends upward gradually as temperature exhibits baseline fluctuations | [
"vibration trends upward gradually as temperature exhibits baseline fluctuations"
] | [
"MCQ_obs"
] | [
"vibration trends upward gradually as temperature exhibits baseline fluctuations",
"a sharp temperature increase appears while vibration stays within its normal range",
"temperature and vibration show a coordinated, slow increase",
"temperature shows a gradual rise while vibration remains within its normal ba... | 0 |
[
[
-0.17309006434512703,
-0.021093238596697,
-0.20077046026515602,
-0.418885129979283,
-2.5225602108524052,
-0.46513590963925705,
-0.5691650778132771,
-0.515346067736007,
-0.460791085761784,
-0.42918639746590104,
-0.072775006334392,
-0.433986671829434,
-0.539242181... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["sudden mechanical imbalance occurrence without corresponding heat buildup", "sudden belt strike against structure causing immediate friction spike and dynamic shock", "slow alignment drift with increasing dynamics", "scheduled maintenance stop followed by system recovery with load engagement"] | how_happened | slow alignment drift with increasing dynamics | [
"slow alignment drift with increasing dynamics"
] | [
"MCQ_cause"
] | [
"sudden mechanical imbalance occurrence without corresponding heat buildup",
"sudden belt strike against structure causing immediate friction spike and dynamic shock",
"slow alignment drift with increasing dynamics",
"scheduled maintenance stop followed by system recovery with load engagement"
] | 2 |
[
[
-0.17309006434512703,
-0.021093238596697,
-0.20077046026515602,
-0.418885129979283,
-2.5225602108524052,
-0.46513590963925705,
-0.5691650778132771,
-0.515346067736007,
-0.460791085761784,
-0.42918639746590104,
-0.072775006334392,
-0.433986671829434,
-0.539242181... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["inspect the roller for any signs of impact damage and surface resistance", "urgently examine the gears for any signs of rapid wear advancement and carry out necessary repairs", "continue to observe the gradual decrease in lubrication and take action if the dynamics show changes", "monitor for any gradual alignment shifts and prepare for an accuracy alignment review"] | suggested_fix | monitor for any gradual alignment shifts and prepare for an accuracy alignment review | [
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review"
] | [
"MCQ_fix"
] | [
"inspect the roller for any signs of impact damage and surface resistance",
"urgently examine the gears for any signs of rapid wear advancement and carry out necessary repairs",
"continue to observe the gradual decrease in lubrication and take action if the dynamics show changes",
"monitor for any gradual ali... | 3 |
[
[
-0.11809250326399401,
-0.447714246052809,
0.012328463628179001,
-0.21671943878730202,
0.042500461039753,
-0.272197331738577,
0.086298471895128,
-0.43863023709027604,
0.039904587906386006,
-0.679357248099532,
-0.065210483446087,
0.04996243604499501,
0.05190856739... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a transient spike in vibration is observed, which quickly subsides while the temperature remains unaffected.", "a sudden increase in temperature is observed while vibration remains within its normal limits", "vibration increases slowly over an extended period, while temperature stays consistent without a clear trend", "vibration climbs rapidly with temperature remaining consistent"] | what_happened | vibration increases slowly over an extended period, while temperature stays consistent without a clear trend | [
"vibration increases slowly over an extended period, while temperature stays consistent without a clear trend"
] | [
"MCQ_obs"
] | [
"a transient spike in vibration is observed, which quickly subsides while the temperature remains unaffected.",
"a sudden increase in temperature is observed while vibration remains within its normal limits",
"vibration increases slowly over an extended period, while temperature stays consistent without a clear... | 2 |
[
[
-0.11809250326399401,
-0.447714246052809,
0.012328463628179001,
-0.21671943878730202,
0.042500461039753,
-0.272197331738577,
0.086298471895128,
-0.43863023709027604,
0.039904587906386006,
-0.679357248099532,
-0.065210483446087,
0.04996243604499501,
0.05190856739... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["incremental imbalance formation in mechanical systems", "foreign material collision that gets stuck and sustains persistent rubbing contact", "a sudden increase in friction along the rolling path with negligible dynamic variation", "abrupt roller lock under load with immediate friction surge and dynamic impact"] | how_happened | incremental imbalance formation in mechanical systems | [
"incremental imbalance formation in mechanical systems"
] | [
"MCQ_cause"
] | [
"incremental imbalance formation in mechanical systems",
"foreign material collision that gets stuck and sustains persistent rubbing contact",
"a sudden increase in friction along the rolling path with negligible dynamic variation",
"abrupt roller lock under load with immediate friction surge and dynamic impa... | 0 |
[
[
-0.11809250326399401,
-0.447714246052809,
0.012328463628179001,
-0.21671943878730202,
0.042500461039753,
-0.272197331738577,
0.086298471895128,
-0.43863023709027604,
0.039904587906386006,
-0.679357248099532,
-0.065210483446087,
0.04996243604499501,
0.05190856739... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor for early signs of heat increase and schedule an inspection", "inspect for an object that may have struck and lodged, then clear the conveyor path to stop rubbing", "monitor restart with immediate load application", "monitor for any gradual alignment shifts and prepare for an accuracy alignment review"] | suggested_fix | monitor for any gradual alignment shifts and prepare for an accuracy alignment review | [
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review"
] | [
"MCQ_fix"
] | [
"monitor for early signs of heat increase and schedule an inspection",
"inspect for an object that may have struck and lodged, then clear the conveyor path to stop rubbing",
"monitor restart with immediate load application",
"monitor for any gradual alignment shifts and prepare for an accuracy alignment revie... | 3 |
[
[
-0.047474921736227006,
-0.546039533586698,
-0.5530555457780421,
-0.553562247895801,
-0.023893362957119003,
-0.012862683209323001,
-0.7197244696164931,
-0.014928475914822001,
-0.018124672024342002,
-0.717502735617044,
-0.716567270809749,
-0.036210336581663005,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration drops to a low level then both vibration and temperature rise together", "temperature and vibration readings show a simultaneous jump", "vibration elevates gradually over time, with temperature hovering around its baseline level", "vibration spikes once and returns, followed by a sharp rise in temperature"] | what_happened | vibration elevates gradually over time, with temperature hovering around its baseline level | [
"vibration elevates gradually over time, with temperature hovering around its baseline level"
] | [
"MCQ_obs"
] | [
"vibration drops to a low level then both vibration and temperature rise together",
"temperature and vibration readings show a simultaneous jump",
"vibration elevates gradually over time, with temperature hovering around its baseline level",
"vibration spikes once and returns, followed by a sharp rise in temp... | 2 |
[
[
-0.047474921736227006,
-0.546039533586698,
-0.5530555457780421,
-0.553562247895801,
-0.023893362957119003,
-0.012862683209323001,
-0.7197244696164931,
-0.014928475914822001,
-0.018124672024342002,
-0.717502735617044,
-0.716567270809749,
-0.036210336581663005,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["sudden impact event followed by trapped material causing continuous rubbing against components", "rapid structural imbalance with negligible heat change", "slow lubrication depletion with negligible dynamic impact", "steady alignment shift due to heightened dynamics"] | how_happened | steady alignment shift due to heightened dynamics | [
"steady alignment shift due to heightened dynamics"
] | [
"MCQ_cause"
] | [
"sudden impact event followed by trapped material causing continuous rubbing against components",
"rapid structural imbalance with negligible heat change",
"slow lubrication depletion with negligible dynamic impact",
"steady alignment shift due to heightened dynamics"
] | 3 |
[
[
-0.047474921736227006,
-0.546039533586698,
-0.5530555457780421,
-0.553562247895801,
-0.023893362957119003,
-0.012862683209323001,
-0.7197244696164931,
-0.014928475914822001,
-0.018124672024342002,
-0.717502735617044,
-0.716567270809749,
-0.036210336581663005,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 164 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor for any gradual alignment shifts and prepare for an accuracy alignment review", "keep an eye on the progressive wear of gears and organize a gear check", "monitor for early signs of heat increase and schedule an inspection", "assess the quality of splice rework and confirm that the belt joint is balanced"] | suggested_fix | monitor for any gradual alignment shifts and prepare for an accuracy alignment review | [
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review"
] | [
"MCQ_fix"
] | [
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review",
"keep an eye on the progressive wear of gears and organize a gear check",
"monitor for early signs of heat increase and schedule an inspection",
"assess the quality of splice rework and confirm that the belt joint is bala... | 0 |
[
[
-1.548420620878741,
-0.886821483031601,
-1.018518080933297,
-0.004689299235414,
-0.9466363233044861,
-1.522270656254714,
-0.9162400384604641,
-0.9713199123090701,
-0.8008871957616971,
-1.501894495558572,
-1.4870477064365262,
-0.7883621498284951,
-0.2023717074955... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration ceases, then both vibration and temperature ramp up together", "temperature and vibration experience a sharp concurrent rise", "a coordinated gentle rise appears in vibration and temperature", "vibration climbs slowly over time while temperature shows no clear trend"] | what_happened | vibration climbs slowly over time while temperature shows no clear trend | [
"vibration climbs slowly over time while temperature shows no clear trend"
] | [
"MCQ_obs"
] | [
"vibration ceases, then both vibration and temperature ramp up together",
"temperature and vibration experience a sharp concurrent rise",
"a coordinated gentle rise appears in vibration and temperature",
"vibration climbs slowly over time while temperature shows no clear trend"
] | 3 |
[
[
-1.548420620878741,
-0.886821483031601,
-1.018518080933297,
-0.004689299235414,
-0.9466363233044861,
-1.522270656254714,
-0.9162400384604641,
-0.9713199123090701,
-0.8008871957616971,
-1.501894495558572,
-1.4870477064365262,
-0.7883621498284951,
-0.2023717074955... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["temporary suspension of operation followed by restart and load ramp-up", "short-lived object contact that moves through", "sudden mechanical imbalance occurrence without corresponding heat buildup", "progressive structural looseness"] | how_happened | progressive structural looseness | [
"progressive structural looseness"
] | [
"MCQ_cause"
] | [
"temporary suspension of operation followed by restart and load ramp-up",
"short-lived object contact that moves through",
"sudden mechanical imbalance occurrence without corresponding heat buildup",
"progressive structural looseness"
] | 3 |
[
[
-1.548420620878741,
-0.886821483031601,
-1.018518080933297,
-0.004689299235414,
-0.9466363233044861,
-1.522270656254714,
-0.9162400384604641,
-0.9713199123090701,
-0.8008871957616971,
-1.501894495558572,
-1.4870477064365262,
-0.7883621498284951,
-0.2023717074955... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["continue monitoring gradual imbalance development and schedule balancing service", "check belt tracking immediately for fresh rub marks and remove contact points", "evaluate temperature control systems to ensure they remain stable", "check for potential resonance causing gradual increases in acceleration and velocity"] | suggested_fix | continue monitoring gradual imbalance development and schedule balancing service | [
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance"
] | [
"MCQ_fix"
] | [
"continue monitoring gradual imbalance development and schedule balancing service",
"check belt tracking immediately for fresh rub marks and remove contact points",
"evaluate temperature control systems to ensure they remain stable",
"check for potential resonance causing gradual increases in acceleration and... | 0 |
[
[
-0.646403245873524,
-0.12306779528117301,
-6.050465690354396,
-0.34220766489221405,
-5.999650631675522,
0.20564224576145101,
-0.046051217753792006,
-6.05175591614315,
-6.05175591614315,
-0.19998498986235902,
0.012406304449949002,
-0.029476508589169004,
-0.028484... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration rises steeply while temperature stays near prior levels", "vibration steadily ascends over time, and temperature maintains a baseline pattern", "there is a temporary spike in vibration that normalizes as the temperature continues at its usual level.", "temperature experiences a sharp increase while vibration persists at baseline values"] | what_happened | vibration steadily ascends over time, and temperature maintains a baseline pattern | [
"vibration steadily ascends over time, and temperature maintains a baseline pattern"
] | [
"MCQ_obs"
] | [
"vibration rises steeply while temperature stays near prior levels",
"vibration steadily ascends over time, and temperature maintains a baseline pattern",
"there is a temporary spike in vibration that normalizes as the temperature continues at its usual level.",
"temperature experiences a sharp increase while... | 1 |
[
[
-0.646403245873524,
-0.12306779528117301,
-6.050465690354396,
-0.34220766489221405,
-5.999650631675522,
0.20564224576145101,
-0.046051217753792006,
-6.05175591614315,
-6.05175591614315,
-0.19998498986235902,
0.012406304449949002,
-0.029476508589169004,
-0.028484... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["quick onset of wear in bearings or gears", "progressive structural looseness", "steady wearing down of gear teeth", "initial contact shock followed by sustained belt rubbing against structure"] | how_happened | progressive structural looseness | [
"progressive structural looseness"
] | [
"MCQ_cause"
] | [
"quick onset of wear in bearings or gears",
"progressive structural looseness",
"steady wearing down of gear teeth",
"initial contact shock followed by sustained belt rubbing against structure"
] | 1 |
[
[
-0.646403245873524,
-0.12306779528117301,
-6.050465690354396,
-0.34220766489221405,
-5.999650631675522,
0.20564224576145101,
-0.046051217753792006,
-6.05175591614315,
-6.05175591614315,
-0.19998498986235902,
0.012406304449949002,
-0.029476508589169004,
-0.028484... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["inspect belt tracking immediately and remove contact against structure", "monitor for any gradual alignment shifts and prepare for an accuracy alignment review", "re-evaluate the adjustment of the belt tension", "monitor the steady wear of bearings and plan for their replacement"] | suggested_fix | monitor for any gradual alignment shifts and prepare for an accuracy alignment review | [
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review"
] | [
"MCQ_fix"
] | [
"inspect belt tracking immediately and remove contact against structure",
"monitor for any gradual alignment shifts and prepare for an accuracy alignment review",
"re-evaluate the adjustment of the belt tension",
"monitor the steady wear of bearings and plan for their replacement"
] | 1 |
[
[
-0.165515464412326,
-0.298173937704445,
-0.043193969288826004,
-0.107308055356631,
-0.297189295937475,
-0.17511396125571702,
-0.12859755949693602,
-0.32192445946732,
-0.24968825241172501,
-0.081711770376828,
-0.102754820677964,
-0.219169345391928,
-0.11616836427... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature trends upward at a gradual pace as vibration remains within acceptable levels", "vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations", "vibration reaches to a newly established stable band", "both vibration and temperature gradually rise in a coordinated manner"] | what_happened | vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations | [
"vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations"
] | [
"MCQ_obs"
] | [
"temperature trends upward at a gradual pace as vibration remains within acceptable levels",
"vibration gradually rises, and temperature continues to exhibit baseline-level fluctuations",
"vibration reaches to a newly established stable band",
"both vibration and temperature gradually rise in a coordinated ma... | 1 |
[
[
-0.165515464412326,
-0.298173937704445,
-0.043193969288826004,
-0.107308055356631,
-0.297189295937475,
-0.17511396125571702,
-0.12859755949693602,
-0.32192445946732,
-0.24968825241172501,
-0.081711770376828,
-0.102754820677964,
-0.219169345391928,
-0.11616836427... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["incremental imbalance formation in mechanical systems", "incremental degradation of gear", "sudden imbalance event in mechanics with negligible thermal change", "rapid friction onset across the bearing surface while dynamics maintain baseline"] | how_happened | incremental imbalance formation in mechanical systems | [
"incremental imbalance formation in mechanical systems"
] | [
"MCQ_cause"
] | [
"incremental imbalance formation in mechanical systems",
"incremental degradation of gear",
"sudden imbalance event in mechanics with negligible thermal change",
"rapid friction onset across the bearing surface while dynamics maintain baseline"
] | 0 |
[
[
-0.165515464412326,
-0.298173937704445,
-0.043193969288826004,
-0.107308055356631,
-0.297189295937475,
-0.17511396125571702,
-0.12859755949693602,
-0.32192445946732,
-0.24968825241172501,
-0.081711770376828,
-0.102754820677964,
-0.219169345391928,
-0.11616836427... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["check the roller for damage from strikes and assess surface drag", "verify belt replacement or reset was performed correctly", "continue monitoring gradual imbalance development and schedule balancing service", "immediately look for any severe structural looseness and secure or repair as needed"] | suggested_fix | continue monitoring gradual imbalance development and schedule balancing service | [
"continue monitoring gradual imbalance development and schedule balancing service"
] | [
"MCQ_fix"
] | [
"check the roller for damage from strikes and assess surface drag",
"verify belt replacement or reset was performed correctly",
"continue monitoring gradual imbalance development and schedule balancing service",
"immediately look for any severe structural looseness and secure or repair as needed"
] | 2 |
[
[
-0.26948352302933204,
1.041813546006194,
0.8137803346469981,
-1.088431091322577,
1.07812160068771,
0.8984326686597051,
0.968721834249571,
0.9055640795629201,
-0.35501159306004504,
0.8539921232751151,
-0.174947166618434,
0.94547554425108,
-0.500043953780772,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration gradually rises over many hours while temperature remains near baseline", "temperature rises sharply while vibration stays near baseline", "vibration subsides, and then both vibration and temperature start to increase concurrently", "vibration and temperature exhibit a parallel jump"] | what_happened | vibration gradually rises over many hours while temperature remains near baseline | [
"vibration gradually rises over many hours while temperature remains near baseline"
] | [
"MCQ_obs"
] | [
"vibration gradually rises over many hours while temperature remains near baseline",
"temperature rises sharply while vibration stays near baseline",
"vibration subsides, and then both vibration and temperature start to increase concurrently",
"vibration and temperature exhibit a parallel jump"
] | 0 |
[
[
-0.26948352302933204,
1.041813546006194,
0.8137803346469981,
-1.088431091322577,
1.07812160068771,
0.8984326686597051,
0.968721834249571,
0.9055640795629201,
-0.35501159306004504,
0.8539921232751151,
-0.174947166618434,
0.94547554425108,
-0.500043953780772,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["steady alignment shift due to heightened dynamics", "a sudden increase in friction along the rolling path with negligible dynamic variation", "initial contact shock followed by sustained belt rubbing against structure", "rapid structural imbalance with negligible heat change"] | how_happened | steady alignment shift due to heightened dynamics | [
"steady alignment shift due to heightened dynamics"
] | [
"MCQ_cause"
] | [
"steady alignment shift due to heightened dynamics",
"a sudden increase in friction along the rolling path with negligible dynamic variation",
"initial contact shock followed by sustained belt rubbing against structure",
"rapid structural imbalance with negligible heat change"
] | 0 |
[
[
-0.26948352302933204,
1.041813546006194,
0.8137803346469981,
-1.088431091322577,
1.07812160068771,
0.8984326686597051,
0.968721834249571,
0.9055640795629201,
-0.35501159306004504,
0.8539921232751151,
-0.174947166618434,
0.94547554425108,
-0.500043953780772,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["check conveyor for transient debris contact", "ensure continuous monitoring of slow imbalance changes and set up balancing maintenance", "maintain surveillance of early heat rise and arrange for inspection", "monitor restart with immediate load application"] | suggested_fix | ensure continuous monitoring of slow imbalance changes and set up balancing maintenance | [
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance"
] | [
"MCQ_fix"
] | [
"check conveyor for transient debris contact",
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance",
"maintain surveillance of early heat rise and arrange for inspection",
"monitor restart with immediate load application"
] | 1 |
[
[
0.7194007820100801,
-0.08812304016692,
0.19912736306952503,
1.715041637845563,
0.33470189263215,
-0.344871800568882,
0.007624400586656001,
0.34233033370666305,
0.5575590408873841,
1.243912672712906,
0.764310804543566,
-34.650753904649285,
-34.54907168169223,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a parallel jump is detected in both vibration and temperature readings", "temperature increases slowly, while vibration continues to follow typical patterns", "a coordinated sharp rise occurs in both vibration and temperature", "vibration gradually rises over many hours while temperature remains near baseline"] | what_happened | temperature increases slowly, while vibration continues to follow typical patterns | [
"temperature increases slowly, while vibration continues to follow typical patterns"
] | [
"MCQ_obs"
] | [
"a parallel jump is detected in both vibration and temperature readings",
"temperature increases slowly, while vibration continues to follow typical patterns",
"a coordinated sharp rise occurs in both vibration and temperature",
"vibration gradually rises over many hours while temperature remains near baselin... | 1 |
[
[
0.7194007820100801,
-0.08812304016692,
0.19912736306952503,
1.715041637845563,
0.33470189263215,
-0.344871800568882,
0.007624400586656001,
0.34233033370666305,
0.5575590408873841,
1.243912672712906,
0.764310804543566,
-34.650753904649285,
-34.54907168169223,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["ongoing friction increase without dynamic disturbance", "quick hit from a foreign object that exits immediately", "slow degradation caused by gear wear", "immediate belt-to-structure collision triggering sharp friction and dynamic jump"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"ongoing friction increase without dynamic disturbance",
"quick hit from a foreign object that exits immediately",
"slow degradation caused by gear wear",
"immediate belt-to-structure collision triggering sharp friction and dynamic jump"
] | 0 |
[
[
0.7194007820100801,
-0.08812304016692,
0.19912736306952503,
1.715041637845563,
0.33470189263215,
-0.344871800568882,
0.007624400586656001,
0.34233033370666305,
0.5575590408873841,
1.243912672712906,
0.764310804543566,
-34.650753904649285,
-34.54907168169223,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["track slow wearing-related deterioration and schedule inspection", "ensure that the belt has been replaced or reset properly", "maintain surveillance of early heat rise and arrange for inspection", "track progressive structural looseness and schedule inspection before progression"] | suggested_fix | maintain surveillance of early heat rise and arrange for inspection | [
"maintain surveillance of early heat rise and arrange for inspection"
] | [
"MCQ_fix"
] | [
"track slow wearing-related deterioration and schedule inspection",
"ensure that the belt has been replaced or reset properly",
"maintain surveillance of early heat rise and arrange for inspection",
"track progressive structural looseness and schedule inspection before progression"
] | 2 |
[
[
-0.6606235460975081,
0.5529332665256791,
-0.7609414312465811,
0.41548986786325304,
-0.66281772344306,
0.36388267858870904,
-0.7598004582421941,
0.566449352938566,
0.341063296970941,
1.049519809806196,
-0.657727232524512,
0.44506739731409406,
-0.6553575178525161,... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a coordinated abrupt increase is noted in both temperature and vibration", "a rapid transition yields a different sustained vibration level", "temperature trends upward at a gradual pace as vibration remains within acceptable levels", "temperature experiences a sharp increase while vibration persists at baseline values"] | what_happened | temperature trends upward at a gradual pace as vibration remains within acceptable levels | [
"temperature trends upward at a gradual pace as vibration remains within acceptable levels"
] | [
"MCQ_obs"
] | [
"a coordinated abrupt increase is noted in both temperature and vibration",
"a rapid transition yields a different sustained vibration level",
"temperature trends upward at a gradual pace as vibration remains within acceptable levels",
"temperature experiences a sharp increase while vibration persists at base... | 2 |
[
[
-0.6606235460975081,
0.5529332665256791,
-0.7609414312465811,
0.41548986786325304,
-0.66281772344306,
0.36388267858870904,
-0.7598004582421941,
0.566449352938566,
0.341063296970941,
1.049519809806196,
-0.657727232524512,
0.44506739731409406,
-0.6553575178525161,... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["slow lubrication depletion with negligible dynamic impact", "operational pause followed by restart with typical conditioning", "ongoing imbalance emergence within mechanical components", "severe roller heating event with minimal change in dynamics"] | how_happened | slow lubrication depletion with negligible dynamic impact | [
"slow lubrication depletion with negligible dynamic impact"
] | [
"MCQ_cause"
] | [
"slow lubrication depletion with negligible dynamic impact",
"operational pause followed by restart with typical conditioning",
"ongoing imbalance emergence within mechanical components",
"severe roller heating event with minimal change in dynamics"
] | 0 |
[
[
-0.6606235460975081,
0.5529332665256791,
-0.7609414312465811,
0.41548986786325304,
-0.66281772344306,
0.36388267858870904,
-0.7598004582421941,
0.566449352938566,
0.341063296970941,
1.049519809806196,
-0.657727232524512,
0.44506739731409406,
-0.6553575178525161,... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["identify any momentary impacts from stray items", "track frictional losses and schedule maintenance before condition worsens", "quickly check rollers for potential lock-up when loaded", "immediately inspect for unexpected imbalance and carry out necessary balancing corrections"] | suggested_fix | track frictional losses and schedule maintenance before condition worsens | [
"track frictional losses and schedule maintenance before condition worsens"
] | [
"MCQ_fix"
] | [
"identify any momentary impacts from stray items",
"track frictional losses and schedule maintenance before condition worsens",
"quickly check rollers for potential lock-up when loaded",
"immediately inspect for unexpected imbalance and carry out necessary balancing corrections"
] | 1 |
[
[
0.8723220556826901,
0.721819157049142,
-0.590382765904869,
1.178195389812706,
-0.297895964138223,
3.889411488082108,
0.8229657864140401,
1.165079025411393,
4.498048968005539,
0.697749061527512,
0.09032894941401601,
0.861503730939537,
1.009302370783433,
0.894... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["an abrupt rise in temperature occurs as vibration remains at normal levels", "vibration and temperature climb together slowly", "temperature drifts upward slowly whereas vibration stays within typical fluctuations", "vibration pauses, after which both vibration and temperature increase simultaneously"] | what_happened | temperature drifts upward slowly whereas vibration stays within typical fluctuations | [
"temperature drifts upward slowly whereas vibration stays within typical fluctuations"
] | [
"MCQ_obs"
] | [
"an abrupt rise in temperature occurs as vibration remains at normal levels",
"vibration and temperature climb together slowly",
"temperature drifts upward slowly whereas vibration stays within typical fluctuations",
"vibration pauses, after which both vibration and temperature increase simultaneously"
] | 2 |
[
[
0.8723220556826901,
0.721819157049142,
-0.590382765904869,
1.178195389812706,
-0.297895964138223,
3.889411488082108,
0.8229657864140401,
1.165079025411393,
4.498048968005539,
0.697749061527512,
0.09032894941401601,
0.861503730939537,
1.009302370783433,
0.894... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["lubrication degradation with minimal dynamic variation", "transient touch by an external body that does not linger", "modifications in operational conditions from belt tension adjustment", "planned shutdown followed by controlled restart and load application"] | how_happened | lubrication degradation with minimal dynamic variation | [
"lubrication degradation with minimal dynamic variation"
] | [
"MCQ_cause"
] | [
"lubrication degradation with minimal dynamic variation",
"transient touch by an external body that does not linger",
"modifications in operational conditions from belt tension adjustment",
"planned shutdown followed by controlled restart and load application"
] | 0 |
[
[
0.8723220556826901,
0.721819157049142,
-0.590382765904869,
1.178195389812706,
-0.297895964138223,
3.889411488082108,
0.8229657864140401,
1.165079025411393,
4.498048968005539,
0.697749061527512,
0.09032894941401601,
0.861503730939537,
1.009302370783433,
0.894... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["re-evaluate the adjustment of the belt tension", "maintain observation of incremental imbalance formation and arrange for balancing service", "immediately check for roller lock-up when under load", "continue monitoring early heat accumulation and plan inspection"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"re-evaluate the adjustment of the belt tension",
"maintain observation of incremental imbalance formation and arrange for balancing service",
"immediately check for roller lock-up when under load",
"continue monitoring early heat accumulation and plan inspection"
] | 3 |
[
[
0.272742308338531,
0.5957662548147701,
-0.13764096283771401,
14.982534690415086,
-0.7745469599337591,
-0.618113918637602,
-0.46066490931395304,
-0.476917975899163,
-3.051969506085113,
3.88797250369018,
0.626240451930207,
-0.178272721105243,
3.591358882219412,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration shows a one-off spike and returns to baseline, then temperature shows a gradual rise", "a parallel jump is detected in both acceleration and temperature readings", "temperature shows a gradual rise while vibration remains within its normal band", "temperature stabilizes within a different consistent range while acceleration jumps"] | what_happened | temperature shows a gradual rise while vibration remains within its normal band | [
"a parallel jump is detected in both vibration and temperature readings"
] | [
"MCQ_obs"
] | [
"vibration shows a one-off spike and returns to baseline, then temperature shows a gradual rise",
"a parallel jump is detected in both acceleration and temperature readings",
"temperature shows a gradual rise while vibration remains within its normal band",
"temperature stabilizes within a different consisten... | 2 |
[
[
0.272742308338531,
0.5957662548147701,
-0.13764096283771401,
14.982534690415086,
-0.7745469599337591,
-0.618113918637602,
-0.46066490931395304,
-0.476917975899163,
-3.051969506085113,
3.88797250369018,
0.626240451930207,
-0.178272721105243,
3.591358882219412,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["slow wearing-related deterioration in bearing and gear", "system halt followed by reactivation with immediate operational capacity", "ongoing friction increase without dynamic disturbance", "sudden belt strike against structure causing immediate friction spike and dynamic shock"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"slow wearing-related deterioration in bearing and gear",
"system halt followed by reactivation with immediate operational capacity",
"ongoing friction increase without dynamic disturbance",
"sudden belt strike against structure causing immediate friction spike and dynamic shock"
] | 2 |
[
[
0.272742308338531,
0.5957662548147701,
-0.13764096283771401,
14.982534690415086,
-0.7745469599337591,
-0.618113918637602,
-0.46066490931395304,
-0.476917975899163,
-3.051969506085113,
3.88797250369018,
0.626240451930207,
-0.178272721105243,
3.591358882219412,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["continue monitoring early heat accumulation and plan inspection", "monitor restart with immediate load application", "check the roller for damage from strikes and assess surface drag", "continue monitoring gradual imbalance development and schedule balancing service"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"continue monitoring early heat accumulation and plan inspection",
"monitor restart with immediate load application",
"check the roller for damage from strikes and assess surface drag",
"continue monitoring gradual imbalance development and schedule balancing service"
] | 0 |
[
[
-40.195667302975345,
-40.195667302975345,
-0.5327499899233951,
0.43010781181536806,
-0.6842646790279371,
-0.30303229144889104,
-0.9286447134493571,
0.068426176578813,
0.102639264868219,
-0.52786157352782,
-0.06354067342304501,
-0.518087653976478,
-0.503425318029... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a rapid temperature rise is noted while vibration remains stable at its baseline", "temperature increases slowly, while vibration continues to follow typical patterns", "both vibration and temperature readings indicate a parallel jump", "vibration spikes once and returns, followed by a sharp rise in temperature"] | what_happened | temperature increases slowly, while vibration continues to follow typical patterns | [
"temperature increases slowly, while vibration continues to follow typical patterns"
] | [
"MCQ_obs"
] | [
"a rapid temperature rise is noted while vibration remains stable at its baseline",
"temperature increases slowly, while vibration continues to follow typical patterns",
"both vibration and temperature readings indicate a parallel jump",
"vibration spikes once and returns, followed by a sharp rise in temperat... | 1 |
[
[
-40.195667302975345,
-40.195667302975345,
-0.5327499899233951,
0.43010781181536806,
-0.6842646790279371,
-0.30303229144889104,
-0.9286447134493571,
0.068426176578813,
0.102639264868219,
-0.52786157352782,
-0.06354067342304501,
-0.518087653976478,
-0.503425318029... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["lubrication degradation with minimal dynamic variation", "sudden misalignment in structure with steady thermal conditions", "external object strike that subsequently lodges and maintains continuous friction", "steady wearing down of gear teeth"] | how_happened | lubrication degradation with minimal dynamic variation | [
"lubrication degradation with minimal dynamic variation"
] | [
"MCQ_cause"
] | [
"lubrication degradation with minimal dynamic variation",
"sudden misalignment in structure with steady thermal conditions",
"external object strike that subsequently lodges and maintains continuous friction",
"steady wearing down of gear teeth"
] | 0 |
[
[
-40.195667302975345,
-40.195667302975345,
-0.5327499899233951,
0.43010781181536806,
-0.6842646790279371,
-0.30303229144889104,
-0.9286447134493571,
0.068426176578813,
0.102639264868219,
-0.52786157352782,
-0.06354067342304501,
-0.518087653976478,
-0.503425318029... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired", "monitor restart with immediate load application", "maintain surveillance of early heat rise and arrange for inspection", "keep an eye on the progressive wear of gears and organize a gear check"] | suggested_fix | maintain surveillance of early heat rise and arrange for inspection | [
"maintain surveillance of early heat rise and arrange for inspection"
] | [
"MCQ_fix"
] | [
"quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired",
"monitor restart with immediate load application",
"maintain surveillance of early heat rise and arrange for inspection",
"keep an eye on the progressive wear of gears and organize a gear check"
] | 2 |
[
[
-1.025728610132614,
-0.049211327830855,
-1.203276579481341,
0.12447740318184901,
-1.1415207140428891,
-0.676420953791899,
1.556443474158078,
0.19202270127162702,
-0.672560565161291,
-0.170794014687042,
-0.620454521004772,
2.324533128950003,
0.08973965697930801,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a gentle increase is observed in both vibration and temperature simultaneously", "vibration pauses, after which both vibration and temperature increase simultaneously", "temperature trends upward at a gradual pace as vibration remains within acceptable levels", "a singular spike in vibration is followed by a notable rise in temperature"] | what_happened | temperature trends upward at a gradual pace as vibration remains within acceptable levels | [
"temperature trends upward at a gradual pace as vibration remains within acceptable levels"
] | [
"MCQ_obs"
] | [
"a gentle increase is observed in both vibration and temperature simultaneously",
"vibration pauses, after which both vibration and temperature increase simultaneously",
"temperature trends upward at a gradual pace as vibration remains within acceptable levels",
"a singular spike in vibration is followed by a... | 2 |
[
[
-1.025728610132614,
-0.049211327830855,
-1.203276579481341,
0.12447740318184901,
-1.1415207140428891,
-0.676420953791899,
1.556443474158078,
0.19202270127162702,
-0.672560565161291,
-0.170794014687042,
-0.620454521004772,
2.324533128950003,
0.08973965697930801,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["slow lubrication depletion with negligible dynamic impact", "immediate thermal surge in the rolling contact with negligible dynamic response", "steady alignment shift due to heightened dynamics", "rapid deterioration of gear or bearing due to wear"] | how_happened | slow lubrication depletion with negligible dynamic impact | [
"slow lubrication depletion with negligible dynamic impact"
] | [
"MCQ_cause"
] | [
"slow lubrication depletion with negligible dynamic impact",
"immediate thermal surge in the rolling contact with negligible dynamic response",
"steady alignment shift due to heightened dynamics",
"rapid deterioration of gear or bearing due to wear"
] | 0 |
[
[
-1.025728610132614,
-0.049211327830855,
-1.203276579481341,
0.12447740318184901,
-1.1415207140428891,
-0.676420953791899,
1.556443474158078,
0.19202270127162702,
-0.672560565161291,
-0.170794014687042,
-0.620454521004772,
2.324533128950003,
0.08973965697930801,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["maintain surveillance of early heat rise and arrange for inspection", "quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired", "urgently evaluate for major structural looseness and take steps to secure or fix it", "monitor slow alignment drift and plan a precision alignment check"] | suggested_fix | maintain surveillance of early heat rise and arrange for inspection | [
"maintain surveillance of early heat rise and arrange for inspection"
] | [
"MCQ_fix"
] | [
"maintain surveillance of early heat rise and arrange for inspection",
"quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired",
"urgently evaluate for major structural looseness and take steps to secure or fix it",
"monitor slow alignment drift and plan a precision alignment... | 0 |
[
[
-7.132987269715746,
-7.139546368090409,
0.14539270929478001,
-7.118775957777407,
0.46022812810873304,
-7.132987269715746,
-7.118775957777407,
0.403382554562906,
0.11696992252186601,
1.557778655824107,
0.0076522135636750005,
-0.16069713642213102,
-6.8935812785901... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["both vibration and temperature show a sudden simultaneous increase", "temperature shows a gradual rise while vibration remains within its normal band", "vibration gradually rises over many hours while temperature remains near baseline", "a parallel jump is detected in both vibration and temperature readings"] | what_happened | temperature shows a gradual rise while vibration remains within its normal band | [
"temperature shows a gradual rise while vibration remains within its normal band"
] | [
"MCQ_obs"
] | [
"both vibration and temperature show a sudden simultaneous increase",
"temperature shows a gradual rise while vibration remains within its normal band",
"vibration gradually rises over many hours while temperature remains near baseline",
"a parallel jump is detected in both vibration and temperature readings"... | 1 |
[
[
-7.132987269715746,
-7.139546368090409,
0.14539270929478001,
-7.118775957777407,
0.46022812810873304,
-7.132987269715746,
-7.118775957777407,
0.403382554562906,
0.11696992252186601,
1.557778655824107,
0.0076522135636750005,
-0.16069713642213102,
-6.8935812785901... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["gradual lubrication loss with little dynamics change", "transient touch by an external body that does not linger", "accelerated wear affecting gears significantly", "immediate alignment deviation with no thermal response"] | how_happened | gradual lubrication loss with little dynamics change | [
"gradual lubrication loss with little dynamics change"
] | [
"MCQ_cause"
] | [
"gradual lubrication loss with little dynamics change",
"transient touch by an external body that does not linger",
"accelerated wear affecting gears significantly",
"immediate alignment deviation with no thermal response"
] | 0 |
[
[
-7.132987269715746,
-7.139546368090409,
0.14539270929478001,
-7.118775957777407,
0.46022812810873304,
-7.132987269715746,
-7.118775957777407,
0.403382554562906,
0.11696992252186601,
1.557778655824107,
0.0076522135636750005,
-0.16069713642213102,
-6.8935812785901... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["ensure continuous monitoring of slow imbalance changes and set up balancing maintenance", "verify belt alignment for impact evidence and new rubbing marks, then eliminate contact points", "continue monitoring early heat accumulation and plan inspection", "check rollers urgently for lock-up under load"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"ensure continuous monitoring of slow imbalance changes and set up balancing maintenance",
"verify belt alignment for impact evidence and new rubbing marks, then eliminate contact points",
"continue monitoring early heat accumulation and plan inspection",
"check rollers urgently for lock-up under load"
] | 2 |
[
[
-0.679673015724465,
1.123354066046163,
0.79487856417724,
0.79487856417724,
0.43650556947359304,
-0.658146706833018,
-0.679673015724465,
-0.6561535267837391,
-0.45324820466588,
-0.6744907594765951,
0.32648229211900703,
-0.6677139502791101,
-0.640606758040128,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration and temperature experience a parallel and sudden jump", "temperature experiences a sharp increase while vibration persists at baseline values", "a rapid transition yields a different sustained vibration level", "temperature shows a gradual rise while vibration remains within its normal band"] | what_happened | temperature shows a gradual rise while vibration remains within its normal band | [
"temperature shows a gradual rise while vibration remains within its normal band"
] | [
"MCQ_obs"
] | [
"vibration and temperature experience a parallel and sudden jump",
"temperature experiences a sharp increase while vibration persists at baseline values",
"a rapid transition yields a different sustained vibration level",
"temperature shows a gradual rise while vibration remains within its normal band"
] | 3 |
[
[
-0.679673015724465,
1.123354066046163,
0.79487856417724,
0.79487856417724,
0.43650556947359304,
-0.658146706833018,
-0.679673015724465,
-0.6561535267837391,
-0.45324820466588,
-0.6744907594765951,
0.32648229211900703,
-0.6677139502791101,
-0.640606758040128,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["gradual lubrication loss with little dynamics change", "sudden belt strike against structure causing immediate friction spike and dynamic shock", "a sudden increase in friction along the rolling path with negligible dynamic variation", "severe gear wear with rapid progression"] | how_happened | gradual lubrication loss with little dynamics change | [
"gradual lubrication loss with little dynamics change"
] | [
"MCQ_cause"
] | [
"gradual lubrication loss with little dynamics change",
"sudden belt strike against structure causing immediate friction spike and dynamic shock",
"a sudden increase in friction along the rolling path with negligible dynamic variation",
"severe gear wear with rapid progression"
] | 0 |
[
[
-0.679673015724465,
1.123354066046163,
0.79487856417724,
0.79487856417724,
0.43650556947359304,
-0.658146706833018,
-0.679673015724465,
-0.6561535267837391,
-0.45324820466588,
-0.6744907594765951,
0.32648229211900703,
-0.6677139502791101,
-0.640606758040128,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["immediately stop the machine to replace components showing rapid wear", "check rollers urgently for lock-up under load", "monitor for early signs of heat increase and schedule an inspection", "verify belt alignment for impact evidence and eliminate contact points"] | suggested_fix | monitor for early signs of heat increase and schedule an inspection | [
"monitor for early signs of heat increase and schedule an inspection"
] | [
"MCQ_fix"
] | [
"immediately stop the machine to replace components showing rapid wear",
"check rollers urgently for lock-up under load",
"monitor for early signs of heat increase and schedule an inspection",
"verify belt alignment for impact evidence and eliminate contact points"
] | 2 |
[
[
-9.268522398169988,
-9.289804877143023,
-9.268522398169988,
0.47721845201636803,
0.18417517213925902,
-8.954196456358076,
0.6261961707511431,
-9.268522398169988,
0.7096882128810781,
0.7064144169488891,
0.17107803681829,
0.09904476834907101,
0.32332955148525505,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature experiences a slow upward trend, with vibration tracking normally", "vibration adjusts to a new steady band", "temperature and vibration readings show a simultaneous jump", "vibration spikes once and returns, followed by a sharp rise in temperature"] | what_happened | temperature experiences a slow upward trend, with vibration tracking normally | [
"temperature experiences a slow upward trend, with vibration tracking normally"
] | [
"MCQ_obs"
] | [
"temperature experiences a slow upward trend, with vibration tracking normally",
"vibration adjusts to a new steady band",
"temperature and vibration readings show a simultaneous jump",
"vibration spikes once and returns, followed by a sharp rise in temperature"
] | 0 |
[
[
-9.268522398169988,
-9.289804877143023,
-9.268522398169988,
0.47721845201636803,
0.18417517213925902,
-8.954196456358076,
0.6261961707511431,
-9.268522398169988,
0.7096882128810781,
0.7064144169488891,
0.17107803681829,
0.09904476834907101,
0.32332955148525505,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["short encounter with an alien object that quickly departs", "ongoing friction increase without dynamic disturbance", "immediate belt contact impact with structure causing sharp friction and dynamic spike", "sudden misalignment in structure with steady thermal conditions"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"short encounter with an alien object that quickly departs",
"ongoing friction increase without dynamic disturbance",
"immediate belt contact impact with structure causing sharp friction and dynamic spike",
"sudden misalignment in structure with steady thermal conditions"
] | 1 |
[
[
-9.268522398169988,
-9.289804877143023,
-9.268522398169988,
0.47721845201636803,
0.18417517213925902,
-8.954196456358076,
0.6261961707511431,
-9.268522398169988,
0.7096882128810781,
0.7064144169488891,
0.17107803681829,
0.09904476834907101,
0.32332955148525505,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["inspect belt tracking immediately and remove contact against structure", "maintain surveillance of early heat rise and arrange for inspection", "keep tracking gradual misalignment and organize a precision alignment evaluation", "verify belt alignment for impact evidence and new rubbing marks, then eliminate contact points"] | suggested_fix | maintain surveillance of early heat rise and arrange for inspection | [
"maintain surveillance of early heat rise and arrange for inspection"
] | [
"MCQ_fix"
] | [
"inspect belt tracking immediately and remove contact against structure",
"maintain surveillance of early heat rise and arrange for inspection",
"keep tracking gradual misalignment and organize a precision alignment evaluation",
"verify belt alignment for impact evidence and new rubbing marks, then eliminate ... | 1 |
[
[
-0.6790029638280941,
-0.6422368619064931,
-0.6210127992708301,
1.658986585376946,
0.5981174723635131,
-0.081219678326982,
-0.6790029638280941,
1.139916088020991,
0.9600964993580591,
0.967950983226717,
2.113883443326832,
0.5051995417977151,
-0.620177204488925,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a fast climb in vibration is observed without a corresponding temperature change", "a sudden parallel jump is observed in vibration and temperature", "vibration experiences a sudden but brief spike, reverting to normal as the temperature stays constant.", "temperature experiences a slow upward trend, with vibration tracking normally"] | what_happened | temperature experiences a slow upward trend, with vibration tracking normally | [
"temperature experiences a slow upward trend, with vibration tracking normally"
] | [
"MCQ_obs"
] | [
"a fast climb in vibration is observed without a corresponding temperature change",
"a sudden parallel jump is observed in vibration and temperature",
"vibration experiences a sudden but brief spike, reverting to normal as the temperature stays constant.",
"temperature experiences a slow upward trend, with vi... | 3 |
[
[
-0.6790029638280941,
-0.6422368619064931,
-0.6210127992708301,
1.658986585376946,
0.5981174723635131,
-0.081219678326982,
-0.6790029638280941,
1.139916088020991,
0.9600964993580591,
0.967950983226717,
2.113883443326832,
0.5051995417977151,
-0.620177204488925,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["temporary suspension of operation followed by restart and load ramp-up", "gradual misalignment with rising dynamic conditions", "quick onset of wear in bearings or gears", "steady loss of lubrication with limited change in dynamics"] | how_happened | steady loss of lubrication with limited change in dynamics | [
"steady loss of lubrication with limited change in dynamics"
] | [
"MCQ_cause"
] | [
"temporary suspension of operation followed by restart and load ramp-up",
"gradual misalignment with rising dynamic conditions",
"quick onset of wear in bearings or gears",
"steady loss of lubrication with limited change in dynamics"
] | 3 |
[
[
-0.6790029638280941,
-0.6422368619064931,
-0.6210127992708301,
1.658986585376946,
0.5981174723635131,
-0.081219678326982,
-0.6790029638280941,
1.139916088020991,
0.9600964993580591,
0.967950983226717,
2.113883443326832,
0.5051995417977151,
-0.620177204488925,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty", "continue monitoring early heat accumulation and plan inspection", "immediately check for a sudden alignment change and ensure proper machine alignment", "inspect gears urgently for severe wear progression and repair"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty",
"continue monitoring early heat accumulation and plan inspection",
"immediately check for a sudden alignment change and ensure proper machine alignment",
"inspect gears urgently for severe wear progression and repa... | 1 |
[
[
-0.012002623446363,
-0.09001960598330501,
-0.06282619411328,
-0.044259640772865004,
-0.6685832267638141,
-0.7149058171315661,
-0.043134432376894,
0.010689843056706,
1.73719111691468,
0.42609283891533806,
-0.7158435233982711,
1.427373603558852,
0.7655418088183551... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature drifts upward slowly whereas vibration stays within typical fluctuations", "there is a concurrent jump in vibration and temperature", "vibration experiences a sudden but brief spike, reverting to normal as the temperature stays constant.", "vibration pauses, after which both vibration and temperature increase simultaneously"] | what_happened | temperature drifts upward slowly whereas vibration stays within typical fluctuations | [
"temperature drifts upward slowly whereas vibration stays within typical fluctuations"
] | [
"MCQ_obs"
] | [
"temperature drifts upward slowly whereas vibration stays within typical fluctuations",
"there is a concurrent jump in vibration and temperature",
"vibration experiences a sudden but brief spike, reverting to normal as the temperature stays constant.",
"vibration pauses, after which both vibration and tempera... | 0 |
[
[
-0.012002623446363,
-0.09001960598330501,
-0.06282619411328,
-0.044259640772865004,
-0.6685832267638141,
-0.7149058171315661,
-0.043134432376894,
0.010689843056706,
1.73719111691468,
0.42609283891533806,
-0.7158435233982711,
1.427373603558852,
0.7655418088183551... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["belt replacement or reset after servicing", "progressive frictional losses without dynamic excitation", "system halt followed by reactivation with immediate operational capacity", "progressive structural looseness"] | how_happened | progressive frictional losses without dynamic excitation | [
"progressive frictional losses without dynamic excitation"
] | [
"MCQ_cause"
] | [
"belt replacement or reset after servicing",
"progressive frictional losses without dynamic excitation",
"system halt followed by reactivation with immediate operational capacity",
"progressive structural looseness"
] | 1 |
[
[
-0.012002623446363,
-0.09001960598330501,
-0.06282619411328,
-0.044259640772865004,
-0.6685832267638141,
-0.7149058171315661,
-0.043134432376894,
0.010689843056706,
1.73719111691468,
0.42609283891533806,
-0.7158435233982711,
1.427373603558852,
0.7655418088183551... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["keep tracking the progressive deterioration due to wear and schedule an evaluation", "inspect gears urgently for severe wear progression and repair", "keep track of planned stop and restart occurrences", "monitor gradual lubrication loss closely and intervene if dynamics begin to change"] | suggested_fix | monitor gradual lubrication loss closely and intervene if dynamics begin to change | [
"monitor gradual lubrication loss closely and intervene if dynamics begin to change"
] | [
"MCQ_fix"
] | [
"keep tracking the progressive deterioration due to wear and schedule an evaluation",
"inspect gears urgently for severe wear progression and repair",
"keep track of planned stop and restart occurrences",
"monitor gradual lubrication loss closely and intervene if dynamics begin to change"
] | 3 |
[
[
16.4759700452486,
-0.20234699941807802,
-0.551855826744596,
-0.006131381156760001,
0.5457244455878361,
-4.102129956794111,
15.844400781268527,
2.225819734697663,
-0.6744907594765951,
-0.907496492077673,
-0.7909933973522341,
-0.7909933973522341,
15.93637743766732... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature ascends gradually, with vibration staying within its usual range", "both vibration and temperature gradually rise in a coordinated manner", "temperature and vibration experience a sharp concurrent rise", "a fast climb in vibration is observed without a corresponding temperature change"] | what_happened | temperature ascends gradually, with vibration staying within its usual range | [
"temperature ascends gradually, with vibration staying within its usual range"
] | [
"MCQ_obs"
] | [
"temperature ascends gradually, with vibration staying within its usual range",
"both vibration and temperature gradually rise in a coordinated manner",
"temperature and vibration experience a sharp concurrent rise",
"a fast climb in vibration is observed without a corresponding temperature change"
] | 0 |
[
[
16.4759700452486,
-0.20234699941807802,
-0.551855826744596,
-0.006131381156760001,
0.5457244455878361,
-4.102129956794111,
15.844400781268527,
2.225819734697663,
-0.6744907594765951,
-0.907496492077673,
-0.7909933973522341,
-0.7909933973522341,
15.93637743766732... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["steady loss of lubrication with limited change in dynamics", "accelerated wear affecting gears significantly", "abrupt friction surge on the rolling path with minimal dynamics change", "sudden belt strike against structure causing immediate friction spike and dynamic shock"] | how_happened | steady loss of lubrication with limited change in dynamics | [
"slow lubrication depletion with negligible dynamic impact"
] | [
"MCQ_cause"
] | [
"steady loss of lubrication with limited change in dynamics",
"accelerated wear affecting gears significantly",
"abrupt friction surge on the rolling path with minimal dynamics change",
"sudden belt strike against structure causing immediate friction spike and dynamic shock"
] | 0 |
[
[
16.4759700452486,
-0.20234699941807802,
-0.551855826744596,
-0.006131381156760001,
0.5457244455878361,
-4.102129956794111,
15.844400781268527,
2.225819734697663,
-0.6744907594765951,
-0.907496492077673,
-0.7909933973522341,
-0.7909933973522341,
15.93637743766732... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 169 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["record restart events alongside immediate load activation", "review and verify that the splice rework is of high quality and the belt joint is balanced", "immediately look for any severe structural looseness and secure or repair as needed", "continue monitoring early heat accumulation and plan inspection"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"record restart events alongside immediate load activation",
"review and verify that the splice rework is of high quality and the belt joint is balanced",
"immediately look for any severe structural looseness and secure or repair as needed",
"continue monitoring early heat accumulation and plan inspection"
] | 3 |
[
[
0.10280984454870201,
-0.201275752170776,
-0.003185668824992,
1.316256043317936,
0.591084235975963,
-3.345809833445003,
-3.357394024870591,
0.6878125688273841,
-3.396780362026691,
0.516945410852195,
-0.18332035255884901,
-3.404310097241961,
-3.419948788032417,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature rises abruptly as vibration tracking normal", "vibration rises steeply while temperature stays near prior levels", "vibration and temperature increase sharply in parallel", "temperature experiences a slow upward trend, with vibration tracking normally"] | what_happened | temperature experiences a slow upward trend, with vibration tracking normally | [
"temperature experiences a slow upward trend, with vibration tracking normally"
] | [
"MCQ_obs"
] | [
"temperature rises abruptly as vibration tracking normal",
"vibration rises steeply while temperature stays near prior levels",
"vibration and temperature increase sharply in parallel",
"temperature experiences a slow upward trend, with vibration tracking normally"
] | 3 |
[
[
0.10280984454870201,
-0.201275752170776,
-0.003185668824992,
1.316256043317936,
0.591084235975963,
-3.345809833445003,
-3.357394024870591,
0.6878125688273841,
-3.396780362026691,
0.516945410852195,
-0.18332035255884901,
-3.404310097241961,
-3.419948788032417,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["adjustment of belt tension affecting operational conditions", "quick onset of wear in bearings or gears", "immediate alignment deviation with no thermal response", "slow lubrication depletion with negligible dynamic impact"] | how_happened | slow lubrication depletion with negligible dynamic impact | [
"slow lubrication depletion with negligible dynamic impact"
] | [
"MCQ_cause"
] | [
"adjustment of belt tension affecting operational conditions",
"quick onset of wear in bearings or gears",
"immediate alignment deviation with no thermal response",
"slow lubrication depletion with negligible dynamic impact"
] | 3 |
[
[
0.10280984454870201,
-0.201275752170776,
-0.003185668824992,
1.316256043317936,
0.591084235975963,
-3.345809833445003,
-3.357394024870591,
0.6878125688273841,
-3.396780362026691,
0.516945410852195,
-0.18332035255884901,
-3.404310097241961,
-3.419948788032417,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["confirm belt tension has been readjusted", "inspect the roller for strike damage and surface drag", "check conveyor for transient debris contact", "continue monitoring early heat accumulation and plan inspection"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"confirm belt tension has been readjusted",
"inspect the roller for strike damage and surface drag",
"check conveyor for transient debris contact",
"continue monitoring early heat accumulation and plan inspection"
] | 3 |
[
[
-20.699411707077136,
-20.666472618305896,
-20.691303644598403,
0.27770178175153604,
1.097125498379601,
1.282595898455644,
-0.05979611126678001,
0.046114482640234,
0.23310721158147102,
0.84121235056052,
-0.46824177858817606,
2.228201346848035,
-20.726269711233154... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature surges abruptly with vibration maintaining its standard range", "temperature ascends gradually, with vibration staying within its usual range", "both vibration and temperature increase slowly and concurrently", "a coordinated abrupt increase is noted in both temperature and vibration"] | what_happened | temperature ascends gradually, with vibration staying within its usual range | [
"temperature ascends gradually, with vibration staying within its usual range"
] | [
"MCQ_obs"
] | [
"temperature surges abruptly with vibration maintaining its standard range",
"temperature ascends gradually, with vibration staying within its usual range",
"both vibration and temperature increase slowly and concurrently",
"a coordinated abrupt increase is noted in both temperature and vibration"
] | 1 |
[
[
-20.699411707077136,
-20.666472618305896,
-20.691303644598403,
0.27770178175153604,
1.097125498379601,
1.282595898455644,
-0.05979611126678001,
0.046114482640234,
0.23310721158147102,
0.84121235056052,
-0.46824177858817606,
2.228201346848035,
-20.726269711233154... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["incremental imbalance formation in mechanical systems", "quick onset of wear in bearings or gears", "immediate thermal surge in the rolling contact with negligible dynamic response", "ongoing friction increase without dynamic disturbance"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"incremental imbalance formation in mechanical systems",
"quick onset of wear in bearings or gears",
"immediate thermal surge in the rolling contact with negligible dynamic response",
"ongoing friction increase without dynamic disturbance"
] | 3 |
[
[
-20.699411707077136,
-20.666472618305896,
-20.691303644598403,
0.27770178175153604,
1.097125498379601,
1.282595898455644,
-0.05979611126678001,
0.046114482640234,
0.23310721158147102,
0.84121235056052,
-0.46824177858817606,
2.228201346848035,
-20.726269711233154... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 165 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["review and verify that the splice rework is of high quality and the belt joint is balanced", "monitor for early signs of heat increase and schedule an inspection", "immediately scrutinize the roller for intense heat and substitute it if it shows damage", "inspect belt tracking immediately and remove contact against structure"] | suggested_fix | monitor for early signs of heat increase and schedule an inspection | [
"monitor for early signs of heat increase and schedule an inspection"
] | [
"MCQ_fix"
] | [
"review and verify that the splice rework is of high quality and the belt joint is balanced",
"monitor for early signs of heat increase and schedule an inspection",
"immediately scrutinize the roller for intense heat and substitute it if it shows damage",
"inspect belt tracking immediately and remove contact ... | 1 |
[
[
-2.06503619800079,
-2.066597732309256,
-2.065816966010489,
0.530508214955934,
0.362735132409344,
-0.08331232542080001,
-2.065816966010489,
-2.065816966010489,
-2.065816966010489,
-2.067194789091953,
0.265185232235553,
0.47424688736729004,
0.40204898937971806,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 161 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration spikes once and returns, followed by a sharp rise in temperature", "vibration climbs rapidly with temperature remaining consistent", "both vibration and temperature show a sudden jump", "temperature drifts upward slowly whereas vibration stays within typical fluctuations"] | what_happened | temperature drifts upward slowly whereas vibration stays within typical fluctuations | [
"temperature drifts upward slowly whereas vibration stays within typical fluctuations"
] | [
"MCQ_obs"
] | [
"vibration spikes once and returns, followed by a sharp rise in temperature",
"vibration climbs rapidly with temperature remaining consistent",
"both vibration and temperature show a sudden jump",
"temperature drifts upward slowly whereas vibration stays within typical fluctuations"
] | 3 |
[
[
-2.06503619800079,
-2.066597732309256,
-2.065816966010489,
0.530508214955934,
0.362735132409344,
-0.08331232542080001,
-2.065816966010489,
-2.065816966010489,
-2.065816966010489,
-2.067194789091953,
0.265185232235553,
0.47424688736729004,
0.40204898937971806,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 161 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["ongoing friction increase without dynamic disturbance", "modifications in operational conditions from belt tension adjustment", "foreign object impact that becomes trapped and continuously rubs against the structure", "temporary suspension of operation followed by restart and load ramp-up"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"ongoing friction increase without dynamic disturbance",
"modifications in operational conditions from belt tension adjustment",
"foreign object impact that becomes trapped and continuously rubs against the structure",
"temporary suspension of operation followed by restart and load ramp-up"
] | 0 |
[
[
-2.06503619800079,
-2.066597732309256,
-2.065816966010489,
0.530508214955934,
0.362735132409344,
-0.08331232542080001,
-2.065816966010489,
-2.065816966010489,
-2.065816966010489,
-2.067194789091953,
0.265185232235553,
0.47424688736729004,
0.40204898937971806,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 161 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor for brief foreign object strike", "continue monitoring early heat accumulation and plan inspection", "quickly address product obstruction and verify the conveyor route", "urgently evaluate for major structural looseness and take steps to secure or fix it"] | suggested_fix | continue monitoring early heat accumulation and plan inspection | [
"continue monitoring early heat accumulation and plan inspection"
] | [
"MCQ_fix"
] | [
"monitor for brief foreign object strike",
"continue monitoring early heat accumulation and plan inspection",
"quickly address product obstruction and verify the conveyor route",
"urgently evaluate for major structural looseness and take steps to secure or fix it"
] | 1 |
[
[
-0.21910242819963802,
0.283543339761253,
0.9838112320679131,
0.44679595366693403,
0.9795144030917201,
0.7904859366983391,
-12.338445392142766,
-12.394294886351133,
-12.394294886351133,
0.19762084400340202,
-11.427668889631649,
-10.181794941741945,
0,
1.43919... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature increases gradually, while vibration continues to follow typical patterns", "temperature exhibits a rapid increase, while vibration remains at its normal baseline", "vibration remains consistent, with a sudden dip in temperature", "a steady temperature rise occurs with vibration rising in parallel"] | what_happened | temperature increases gradually, while vibration continues to follow typical patterns | [
"temperature increases slowly, while vibration continues to follow typical patterns"
] | [
"MCQ_obs"
] | [
"temperature increases gradually, while vibration continues to follow typical patterns",
"temperature exhibits a rapid increase, while vibration remains at its normal baseline",
"vibration remains consistent, with a sudden dip in temperature",
"a steady temperature rise occurs with vibration rising in paralle... | 0 |
[
[
-0.21910242819963802,
0.283543339761253,
0.9838112320679131,
0.44679595366693403,
0.9795144030917201,
0.7904859366983391,
-12.338445392142766,
-12.394294886351133,
-12.394294886351133,
0.19762084400340202,
-11.427668889631649,
-10.181794941741945,
0,
1.43919... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["progressive frictional losses without dynamic excitation", "transient touch by an external body that does not linger", "progressive structural looseness", "sudden imbalance event in mechanics with negligible thermal change"] | how_happened | progressive frictional losses without dynamic excitation | [
"progressive frictional losses without dynamic excitation"
] | [
"MCQ_cause"
] | [
"progressive frictional losses without dynamic excitation",
"transient touch by an external body that does not linger",
"progressive structural looseness",
"sudden imbalance event in mechanics with negligible thermal change"
] | 0 |
[
[
-0.21910242819963802,
0.283543339761253,
0.9838112320679131,
0.44679595366693403,
0.9795144030917201,
0.7904859366983391,
-12.338445392142766,
-12.394294886351133,
-12.394294886351133,
0.19762084400340202,
-11.427668889631649,
-10.181794941741945,
0,
1.43919... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 167 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["check for severe structural looseness and secure or repair immediately", "monitor restart with immediate load application", "monitor gradual bearing wear and prepare for bearing replacement", "continue tracking slow lubrication depletion and respond when dynamic shifts occur"] | suggested_fix | continue tracking slow lubrication depletion and respond when dynamic shifts occur | [
"continue tracking slow lubrication depletion and respond when dynamic shifts occur"
] | [
"MCQ_fix"
] | [
"check for severe structural looseness and secure or repair immediately",
"monitor restart with immediate load application",
"monitor gradual bearing wear and prepare for bearing replacement",
"continue tracking slow lubrication depletion and respond when dynamic shifts occur"
] | 3 |
[
[
-2.639466332924202,
-2.639466332924202,
-0.22827820993878703,
0.33171662986896705,
-2.627339062322481,
-2.643270980386546,
0.29771272051317804,
0.23897882411112903,
0.49864524716804803,
-2.63471054574217,
0.15717917827986402,
-2.650642463806235,
-2.6480267675685... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["a rapid temperature rise is noted while vibration remains stable at its baseline", "temperature shows a gradual rise while vibration remains within its normal band", "vibration surges rapidly but temperature does not deviate from baseline", "a rapid transition yields a different sustained vibration level"] | what_happened | temperature shows a gradual rise while vibration remains within its normal band | [
"temperature shows a gradual rise while vibration remains within its normal band"
] | [
"MCQ_obs"
] | [
"a rapid temperature rise is noted while vibration remains stable at its baseline",
"temperature shows a gradual rise while vibration remains within its normal band",
"vibration surges rapidly but temperature does not deviate from baseline",
"a rapid transition yields a different sustained vibration level"
] | 1 |
[
[
-2.639466332924202,
-2.639466332924202,
-0.22827820993878703,
0.33171662986896705,
-2.627339062322481,
-2.643270980386546,
0.29771272051317804,
0.23897882411112903,
0.49864524716804803,
-2.63471054574217,
0.15717917827986402,
-2.650642463806235,
-2.6480267675685... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["ongoing imbalance emergence within mechanical components", "an abrupt increase in friction on the rolling track with little dynamic alteration", "ongoing friction increase without dynamic disturbance", "transient touch by an external body that does not linger"] | how_happened | ongoing friction increase without dynamic disturbance | [
"ongoing friction increase without dynamic disturbance"
] | [
"MCQ_cause"
] | [
"ongoing imbalance emergence within mechanical components",
"an abrupt increase in friction on the rolling track with little dynamic alteration",
"ongoing friction increase without dynamic disturbance",
"transient touch by an external body that does not linger"
] | 2 |
[
[
-2.639466332924202,
-2.639466332924202,
-0.22827820993878703,
0.33171662986896705,
-2.627339062322481,
-2.643270980386546,
0.29771272051317804,
0.23897882411112903,
0.49864524716804803,
-2.63471054574217,
0.15717917827986402,
-2.650642463806235,
-2.6480267675685... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["monitor scheduled stop and restart events", "maintain surveillance of early heat rise and arrange for inspection", "track slow wearing-related deterioration and schedule inspection", "inspect the roller for any signs of impact damage and surface resistance"] | suggested_fix | maintain surveillance of early heat rise and arrange for inspection | [
"continue tracking slow lubrication depletion and respond when dynamic shifts occur"
] | [
"MCQ_fix"
] | [
"monitor scheduled stop and restart events",
"maintain surveillance of early heat rise and arrange for inspection",
"track slow wearing-related deterioration and schedule inspection",
"inspect the roller for any signs of impact damage and surface resistance"
] | 1 |
[
[
0.7545491502772861,
0.06604786422909001,
-12.196203990944905,
0.208818203855438,
0.096737172510811,
-0.059376828729269006,
-0.328905591229714,
0.331574641675279,
0.5677458407554831,
-8.68831909647391,
-11.086063268291078,
-11.146106961978216,
0.378275071402207,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["temperature experiences a sharp increase while vibration persists at baseline values", "a coordinated abrupt increase is noted in both temperature and vibration", "vibration decreases to a minimal level and subsequently, both vibration and temperature escalate together", "there is a simultaneous, gradual increase in both vibration and temperature"] | what_happened | temperature experiences a sharp increase while vibration persists at baseline values | [
"temperature experiences a sharp increase while vibration persists at baseline values"
] | [
"MCQ_obs"
] | [
"temperature experiences a sharp increase while vibration persists at baseline values",
"a coordinated abrupt increase is noted in both temperature and vibration",
"vibration decreases to a minimal level and subsequently, both vibration and temperature escalate together",
"there is a simultaneous, gradual inc... | 0 |
[
[
0.7545491502772861,
0.06604786422909001,
-12.196203990944905,
0.208818203855438,
0.096737172510811,
-0.059376828729269006,
-0.328905591229714,
0.331574641675279,
0.5677458407554831,
-8.68831909647391,
-11.086063268291078,
-11.146106961978216,
0.378275071402207,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["foreign material collision that gets stuck and sustains persistent rubbing contact", "a sudden increase in friction along the rolling path with negligible dynamic variation", "temporary debris impact with no sticking", "slow lubrication depletion with negligible dynamic impact"] | how_happened | a sudden increase in friction along the rolling path with negligible dynamic variation | [
"a sudden increase in friction along the rolling path with negligible dynamic variation"
] | [
"MCQ_cause"
] | [
"foreign material collision that gets stuck and sustains persistent rubbing contact",
"a sudden increase in friction along the rolling path with negligible dynamic variation",
"temporary debris impact with no sticking",
"slow lubrication depletion with negligible dynamic impact"
] | 1 |
[
[
0.7545491502772861,
0.06604786422909001,
-12.196203990944905,
0.208818203855438,
0.096737172510811,
-0.059376828729269006,
-0.328905591229714,
0.331574641675279,
0.5677458407554831,
-8.68831909647391,
-11.086063268291078,
-11.146106961978216,
0.378275071402207,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 170 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["maintain surveillance of early heat rise and arrange for inspection", "verify immediately the machine alignment after abrupt alignment shift", "record restart events alongside immediate load activation", "immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"] | suggested_fix | immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty | [
"immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"
] | [
"MCQ_fix"
] | [
"maintain surveillance of early heat rise and arrange for inspection",
"verify immediately the machine alignment after abrupt alignment shift",
"record restart events alongside immediate load activation",
"immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"
] | 3 |
[
[
-0.35564978885778503,
-6.017451656334242,
-6.023807289185721,
0.49017738705325303,
-6.017451656334242,
-6.023807289185721,
-6.017451656334242,
-6.017451656334242,
-6.017451656334242,
0.21847483734237302,
0.312220061820912,
0.13955870597747702,
-0.026216879461163... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration decreases to a minimal level and subsequently, both vibration and temperature escalate together", "temperature experiences a slow upward trend, with vibration tracking normally", "a sudden increase in temperature is observed while vibration remains within its normal limits", "a fast climb in vibration is observed without a corresponding temperature change"] | what_happened | a sudden increase in temperature is observed while vibration remains within its normal limits | [
"a sudden increase in temperature is observed while vibration remains within its normal limits"
] | [
"MCQ_obs"
] | [
"vibration decreases to a minimal level and subsequently, both vibration and temperature escalate together",
"temperature experiences a slow upward trend, with vibration tracking normally",
"a sudden increase in temperature is observed while vibration remains within its normal limits",
"a fast climb in vibrat... | 2 |
[
[
-0.35564978885778503,
-6.017451656334242,
-6.023807289185721,
0.49017738705325303,
-6.017451656334242,
-6.023807289185721,
-6.017451656334242,
-6.017451656334242,
-6.017451656334242,
0.21847483734237302,
0.312220061820912,
0.13955870597747702,
-0.026216879461163... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["planned shutdown followed by controlled restart and load application", "quick onset of wear in bearings or gears", "immediate thermal surge in the rolling contact with negligible dynamic response", "ongoing friction increase without dynamic disturbance"] | how_happened | immediate thermal surge in the rolling contact with negligible dynamic response | [
"immediate thermal surge in the rolling contact with negligible dynamic response"
] | [
"MCQ_cause"
] | [
"planned shutdown followed by controlled restart and load application",
"quick onset of wear in bearings or gears",
"immediate thermal surge in the rolling contact with negligible dynamic response",
"ongoing friction increase without dynamic disturbance"
] | 2 |
[
[
-0.35564978885778503,
-6.017451656334242,
-6.023807289185721,
0.49017738705325303,
-6.017451656334242,
-6.023807289185721,
-6.017451656334242,
-6.017451656334242,
-6.017451656334242,
0.21847483734237302,
0.312220061820912,
0.13955870597747702,
-0.026216879461163... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["inspect conveyor for temporary debris impact", "check immediately the roller showing severe heating and replace if damaged", "verify belt alignment for impact evidence and new rubbing marks, then eliminate contact points", "re-evaluate the adjustment of the belt tension"] | suggested_fix | check immediately the roller showing severe heating and replace if damaged | [
"check immediately the roller showing severe heating and replace if damaged"
] | [
"MCQ_fix"
] | [
"inspect conveyor for temporary debris impact",
"check immediately the roller showing severe heating and replace if damaged",
"verify belt alignment for impact evidence and new rubbing marks, then eliminate contact points",
"re-evaluate the adjustment of the belt tension"
] | 1 |
[
[
-1.203065167738938,
-1.080343146134689,
1.079377819677615,
0.5768919924851751,
1.447545036431243,
0.6609617898165671,
1.096770975018137,
0.14494872087541802,
0.059912445146074,
-14.399104762556346,
0.672558378651128,
-0.165240159468921,
-0.17876855315851,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline", "vibration adjusts to a new steady band", "a parallel jump is detected in both vibration and temperature readings", "temperature rises abruptly as vibration tracking normal"] | what_happened | temperature rises abruptly as vibration tracking normal | [
"temperature rises abruptly as vibration tracking normal"
] | [
"MCQ_obs"
] | [
"vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline",
"vibration adjusts to a new steady band",
"a parallel jump is detected in both vibration and temperature readings",
"temperature rises abruptly as vibration tracking normal"
] | 3 |
[
[
-1.203065167738938,
-1.080343146134689,
1.079377819677615,
0.5768919924851751,
1.447545036431243,
0.6609617898165671,
1.096770975018137,
0.14494872087541802,
0.059912445146074,
-14.399104762556346,
0.672558378651128,
-0.165240159468921,
-0.17876855315851,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["product jam with slip losses and dynamic shock", "abrupt wear-related breakdown in the bearing or gear", "adjustment of belt tension affecting operational conditions", "abrupt friction surge on the rolling path with minimal dynamics change"] | how_happened | abrupt friction surge on the rolling path with minimal dynamics change | [
"an abrupt increase in friction on the rolling track with little dynamic alteration"
] | [
"MCQ_cause"
] | [
"product jam with slip losses and dynamic shock",
"abrupt wear-related breakdown in the bearing or gear",
"adjustment of belt tension affecting operational conditions",
"abrupt friction surge on the rolling path with minimal dynamics change"
] | 3 |
[
[
-1.203065167738938,
-1.080343146134689,
1.079377819677615,
0.5768919924851751,
1.447545036431243,
0.6609617898165671,
1.096770975018137,
0.14494872087541802,
0.059912445146074,
-14.399104762556346,
0.672558378651128,
-0.165240159468921,
-0.17876855315851,
-0... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 168 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["keep track of planned stop and restart occurrences", "quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired", "detect short-lived contact with external objects", "immediately assess for any drastic imbalance and proceed with corrective balancing"] | suggested_fix | quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired | [
"quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired"
] | [
"MCQ_fix"
] | [
"keep track of planned stop and restart occurrences",
"quickly inspect for any abrupt lubrication loss and replace the bearing if it's impaired",
"detect short-lived contact with external objects",
"immediately assess for any drastic imbalance and proceed with corrective balancing"
] | 1 |
[
[
-0.361953287022512,
-0.2930990435859,
-0.8458067216403311,
-0.820981713284726,
-0.8387807795008271,
-0.09941711704468201,
-0.32003183632826804,
-0.8322232241977571,
0.26195068207000605,
-0.8458067216403311,
-0.8387807795008271,
-0.266166250843533,
-0.34509101192... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["vibration reaches to a newly established stable band", "a transient spike in vibration is observed, which quickly subsides while the temperature remains unaffected.", "vibration and temperature both rise sharply", "temperature experiences a sharp increase while vibration persists at baseline values"] | what_happened | temperature experiences a sharp increase while vibration persists at baseline values | [
"temperature experiences a sharp increase while vibration persists at baseline values"
] | [
"MCQ_obs"
] | [
"vibration reaches to a newly established stable band",
"a transient spike in vibration is observed, which quickly subsides while the temperature remains unaffected.",
"vibration and temperature both rise sharply",
"temperature experiences a sharp increase while vibration persists at baseline values"
] | 3 |
[
[
-0.361953287022512,
-0.2930990435859,
-0.8458067216403311,
-0.820981713284726,
-0.8387807795008271,
-0.09941711704468201,
-0.32003183632826804,
-0.8322232241977571,
0.26195068207000605,
-0.8458067216403311,
-0.8387807795008271,
-0.266166250843533,
-0.34509101192... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the most likely cause of the anomalous pattern in these time series?
Choose from: ["rapid friction onset across the bearing surface while dynamics maintain baseline", "rapid deterioration of gear or bearing due to wear", "initial contact shock followed by sustained belt rubbing against structure", "lubrication degradation with minimal dynamic variation"] | how_happened | rapid friction onset across the bearing surface while dynamics maintain baseline | [
"rapid friction onset across the bearing surface while dynamics maintain baseline"
] | [
"MCQ_cause"
] | [
"rapid friction onset across the bearing surface while dynamics maintain baseline",
"rapid deterioration of gear or bearing due to wear",
"initial contact shock followed by sustained belt rubbing against structure",
"lubrication degradation with minimal dynamic variation"
] | 0 |
[
[
-0.361953287022512,
-0.2930990435859,
-0.8458067216403311,
-0.820981713284726,
-0.8387807795008271,
-0.09941711704468201,
-0.32003183632826804,
-0.8322232241977571,
0.26195068207000605,
-0.8458067216403311,
-0.8387807795008271,
-0.266166250843533,
-0.34509101192... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the best corrective action for the event implied by the anomalous pattern in these time series?
Choose from: ["urgently examine the gears for any signs of rapid wear advancement and carry out necessary repairs", "track restart with immediate load pickup", "continue monitoring early heat accumulation and plan inspection", "immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"] | suggested_fix | immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty | [
"immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"
] | [
"MCQ_fix"
] | [
"urgently examine the gears for any signs of rapid wear advancement and carry out necessary repairs",
"track restart with immediate load pickup",
"continue monitoring early heat accumulation and plan inspection",
"immediately evaluate for sudden lubrication breakdown and change the bearing if found faulty"
] | 3 |
[
[
-1.462732092048912,
25.875691083018705,
-2.059050644495064,
-0.25239063019990304,
0.23067674773842803,
-2.28655338366446,
-1.908718129224407,
-0.403725128602265,
-1.7162927645544381,
-1.015411139349778,
-1.539234858185831,
-0.595148510140528,
0.298160072712052,
... | [
"Acceleration",
"Velocity",
"Temperature"
] | You are a sensor time series analysis expert. In a sensor-based warehouse monitoring system, the vibration (measured in velocity and acceleration) and temperature of machines are collected hourly over approximately one week, resulting in three standardized sensor time series of length 166 each (Acceleration, Velocity, and Temperature). Standardization is performed using median and MAD (Median Absolute Deviation).
Based on the provided sensor time series, answer the following question: What is the key anomalous pattern observed in these time series?
Choose from: ["an abrupt rise in temperature occurs as vibration remains at normal levels", "vibration rises abruptly while temperature stays near baseline", "a brief spike in vibration occurs and quickly returns to normal, with the temperature remaining stable.", "vibration shows a slow upward trajectory over several hours, while temperature remains stable around its baseline"] | what_happened | an abrupt rise in temperature occurs as vibration remains at normal levels | [
"an abrupt rise in temperature occurs as vibration remains at normal levels"
] | [
"MCQ_obs"
] | [
"an abrupt rise in temperature occurs as vibration remains at normal levels",
"vibration rises abruptly while temperature stays near baseline",
"a brief spike in vibration occurs and quickly returns to normal, with the temperature remaining stable.",
"vibration shows a slow upward trajectory over several hour... | 0 |
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