Datasets:
file_name stringclasses 5 values | quality stringclasses 5 values | burn_mark_location stringclasses 5 values | burn_mark_shape stringclasses 3 values | burn_mark_size stringclasses 5 values | burn_mark_color_intensity stringclasses 3 values | burn_mark_texture stringclasses 2 values | circuit_damage_assessment stringclasses 5 values | related_components stringclasses 4 values |
|---|---|---|---|---|---|---|---|---|
1dac578bf5dcdf3fb56e85cc0c8b4a58.png | 2797*1500 | Near power switch | Irregular | About 0.5 cm diameter | Dark brown | Rough | May affect power switch function | Power switch |
3af570fd13248de8e3c5bf487dba47a0.png | 1957*1500 | middle right | irregular shape | approximately 2 cm diameter | dark brown | rough | may affect display functionality | display screen |
44654860b3855b778a66f8eb0bac99d5.png | 2295*1500 | upper middle | approximately circular | approximately 1 cm diameter | dark brown | rough | potential local malfunction | possibly related to button |
9de84c082d1a9fbfc3272a673e0ae06f.png | 2253*1500 | bottom center | irregular shape | approximately 5 cm | light brown | rough | slight surface damage, little impact on circuit functionality | display board |
f4178636e538bb9b5edaf9bd3fc3b8a6.png | 2753*1500 | middle slightly right | irregular shape | approximately 1 cm long | dark brown | rough | moderate potential damage to circuit functionality | display board |
Washing Machine Display Board Burn Detection Dataset
The washing machine industry faces significant challenges related to product safety, particularly concerning electrical failures that can lead to fires. Existing solutions often rely on manual inspection, which is inconsistent and not scalable, leaving a gap in proactive failure detection. This dataset aims to address the need for automated detection of burn marks and short circuit traces on display boards, thereby improving safety and reliability in industrial applications. The dataset comprises images collected from various washing machine display boards, captured under controlled lighting conditions to ensure clarity. Quality control measures include multi-round annotations, consistency checks, and expert reviews to maintain high accuracy. The images are stored in JPG format, organized by unique identifiers, and accompanied by metadata for each entry.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| burn_mark_location | string | Describes the specific location of the burn mark on the display board, such as the top left or bottom right corner. |
| burn_mark_shape | string | Describes the shape of the burn mark, such as circular or strip-shaped. |
| burn_mark_size | string | Describes the size of the burn mark, usually indicated by diameter or area. |
| burn_mark_color_intensity | string | Describes the intensity of the burn mark's color, such as light brown or dark brown. |
| burn_mark_texture | string | Describes the texture characteristics of the charred spot, such as smooth or rough. |
| circuit_damage_assessment | string | Evaluates the potential damage to the circuit function caused by the charred spot. |
| related_components | string | Describes the circuit board components related to the charred spot, such as capacitors and resistors. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Source & Contact
If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com
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