Anomaly Agent
Collection
Real-time turbine health monitoring with ML-powered anomaly detection and automated root cause analysis for power generation SCADA systems.
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3 items
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Updated
Datasets:
timestamp
stringdate 2025-01-25 06:00:00
2025-01-25 15:10:00
| exhaust_temp
float64 872
884
| vibration_x
float64 0.16
0.78
| vibration_y
float64 0.14
0.71
| bearing_temp
float64 160
214
| inlet_pressure
float64 194
200
| lube_oil_pressure
float64 20.9
30.3
| fuel_flow
float64 8.02
8.68
|
|---|---|---|---|---|---|---|---|
2025-01-25 06:00:00
| 872.5
| 0.16
| 0.14
| 160.2
| 194.5
| 30.2
| 8.05
|
2025-01-25 06:05:00
| 873.8
| 0.17
| 0.15
| 160.5
| 194.8
| 30.1
| 8.08
|
2025-01-25 06:10:00
| 872.1
| 0.16
| 0.14
| 160.1
| 194.2
| 30.3
| 8.02
|
2025-01-25 06:15:00
| 874.2
| 0.17
| 0.15
| 160.8
| 195.1
| 30
| 8.1
|
2025-01-25 06:20:00
| 873
| 0.16
| 0.14
| 160.4
| 194.6
| 30.2
| 8.06
|
2025-01-25 06:25:00
| 874.5
| 0.17
| 0.15
| 160.9
| 195.2
| 30.1
| 8.12
|
2025-01-25 06:30:00
| 872.8
| 0.16
| 0.14
| 160.3
| 194.4
| 30.2
| 8.04
|
2025-01-25 06:35:00
| 875.1
| 0.18
| 0.16
| 161.2
| 195.5
| 29.9
| 8.15
|
2025-01-25 06:40:00
| 873.5
| 0.17
| 0.15
| 160.6
| 194.9
| 30.1
| 8.08
|
2025-01-25 06:45:00
| 874.8
| 0.17
| 0.15
| 161
| 195.3
| 30
| 8.13
|
2025-01-25 06:50:00
| 873.2
| 0.16
| 0.14
| 160.5
| 194.7
| 30.2
| 8.07
|
2025-01-25 06:55:00
| 875
| 0.18
| 0.16
| 161.1
| 195.4
| 30
| 8.14
|
2025-01-25 07:00:00
| 872.9
| 0.16
| 0.14
| 160.3
| 194.5
| 30.2
| 8.05
|
2025-01-25 07:05:00
| 874.3
| 0.17
| 0.15
| 160.8
| 195
| 30.1
| 8.11
|
2025-01-25 07:10:00
| 873.1
| 0.16
| 0.14
| 160.4
| 194.6
| 30.2
| 8.06
|
2025-01-25 07:15:00
| 874.6
| 0.17
| 0.15
| 160.9
| 195.2
| 30
| 8.12
|
2025-01-25 07:20:00
| 872.7
| 0.16
| 0.14
| 160.2
| 194.3
| 30.3
| 8.03
|
2025-01-25 07:25:00
| 874.9
| 0.18
| 0.16
| 161.1
| 195.4
| 29.9
| 8.14
|
2025-01-25 07:30:00
| 873.4
| 0.17
| 0.15
| 160.6
| 194.8
| 30.1
| 8.08
|
2025-01-25 07:35:00
| 875.2
| 0.18
| 0.16
| 161.3
| 195.6
| 29.9
| 8.16
|
2025-01-25 14:00:00
| 878.2
| 0.24
| 0.21
| 172.5
| 196.2
| 28.8
| 8.22
|
2025-01-25 14:05:00
| 878.8
| 0.26
| 0.23
| 174.2
| 196.5
| 28.5
| 8.25
|
2025-01-25 14:10:00
| 879.1
| 0.28
| 0.25
| 176
| 196.8
| 28.2
| 8.28
|
2025-01-25 14:15:00
| 879.5
| 0.31
| 0.28
| 178.1
| 197
| 27.9
| 8.32
|
2025-01-25 14:20:00
| 879.8
| 0.34
| 0.3
| 180.5
| 197.2
| 27.5
| 8.35
|
2025-01-25 14:25:00
| 880.2
| 0.37
| 0.33
| 183
| 197.5
| 27.1
| 8.38
|
2025-01-25 14:30:00
| 880.5
| 0.4
| 0.36
| 185.8
| 197.8
| 26.6
| 8.42
|
2025-01-25 14:35:00
| 880.9
| 0.44
| 0.39
| 188.5
| 198
| 26.1
| 8.45
|
2025-01-25 14:40:00
| 881.2
| 0.48
| 0.43
| 191.5
| 198.2
| 25.5
| 8.48
|
2025-01-25 14:45:00
| 881.6
| 0.52
| 0.47
| 194.8
| 198.5
| 24.9
| 8.52
|
2025-01-25 14:50:00
| 882
| 0.56
| 0.51
| 198.2
| 198.8
| 24.2
| 8.55
|
2025-01-25 14:55:00
| 882.4
| 0.61
| 0.55
| 201.8
| 199
| 23.5
| 8.58
|
2025-01-25 15:00:00
| 882.8
| 0.66
| 0.6
| 205.5
| 199.2
| 22.7
| 8.62
|
2025-01-25 15:05:00
| 883.2
| 0.72
| 0.65
| 209.5
| 199.5
| 21.8
| 8.65
|
2025-01-25 15:10:00
| 883.6
| 0.78
| 0.71
| 213.8
| 199.8
| 20.9
| 8.68
|
Turbine Sensor Streams Dataset
Production-ready gas turbine telemetry data for anomaly detection. Designed to simulate real enterprise RAG documents for the IoT Anomaly Agent Space.
Overview
This dataset provides realistic sensor streams that mirror actual SCADA exports from power plant DCS systems (Emerson Ovation, ABB Symphony). Use these files to test anomaly detection or upload your own telemetry data.
Files
| File | Description | Status |
|---|---|---|
gt_unit1_baseline_jan2025.csv |
GE 7FA Unit 1 - Normal operation baseline | Normal |
gt_unit2_bearing_event_jan2025.csv |
GE 7FA Unit 2 - Developing bearing issue | Anomaly |
Data Schema
Matches standard SCADA/historian CSV exports:
timestamp - ISO 8601 timestamp (5-minute intervals)
exhaust_temp - Turbine exhaust temperature (F)
vibration_x - X-axis vibration velocity (in/s)
vibration_y - Y-axis vibration velocity (in/s)
bearing_temp - Journal bearing temperature (F)
inlet_pressure - Compressor inlet pressure (psi)
lube_oil_pressure - Lubrication system pressure (psi)
fuel_flow - Natural gas flow rate (MSCF/hr)
Upload Your Own Data
The IoT Anomaly Agent Space accepts CSV uploads with this schema. Export from your historian (PI, PHD, Wonderware) and upload for instant anomaly detection and root cause analysis.
RAG Integration
These documents are indexed for retrieval-augmented generation:
- Asset identification by unit number
- Temporal context for event correlation
- Failure mode pattern matching
- Maintenance history cross-reference
- Downloads last month
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Size of downloaded dataset files:
2.24 kB
Size of the auto-converted Parquet files:
7.2 kB
Number of rows:
35