Power Strip Hot Melt Point Detection Dataset
V1.0Latest Update: | 2026-01-13 | Samples: | 5000 records |
Samples: | 5000 records | ||
File Size: | 1.5G | Format: | JPG/PNG/JSON |
Format: | JPG/PNG/JSON | ||
Data Domain: | Image | Holder: |  MOBIUSI INC |
Holder: | MOBIUSI INC | ||
Industry Scope: | Industrial Inspection | Quality Control | Thermal Analysis | ||
Applications: | Anomaly Detection | Image Classification | ||
Brief Introduction
The current industrial landscape faces significant challenges in ensuring the safety and reliability of electrical components, particularly power strips. Overheating issues often lead to catastrophic failures, yet existing detection solutions tend to lack accuracy and timeliness. This dataset aims to bridge that gap by providing a comprehensive collection of images that identify overheating risks, such as burnt solder points and abnormal soldering conditions. Data is collected using high-resolution thermal cameras in controlled environments, ensuring that images accurately represent the thermal conditions of power strips. Quality control measures include multi-round annotations and expert reviews to enhance consistency and reliability. The dataset is organized in JPG format, with images systematically categorized by their conditions.
Sample Examples
| Image | File Name | Resolution | Overheating Risk Level | Burn Damage Severity | Insulation Condition | Abnormal Area Proportion |
|---|---|---|---|---|---|---|
 | 4333973f2b75c8e85534b396833ac166.png | 1153*1500 | 5 | Severe | Severe Wear | 0.1 |
 | f5bd6cbba96625fed3d2d30f86d4951f.png | 1090*1500 | 4 | Severe | Severe Wear | 0.3 |
 | 4f5c82c52da5a5afe8db121b1cda90dd.png | 1925*1500 | 5 | Severe | Severely Worn | 0.2 |
 | 72acf25cbf63e0eb88664abf5bdef2d3.png | 832*1500 | 4 | Severe | Severely Worn | 0.3 |
 | 48709e30169b0949dffe58e4add6c742.png | 1107*1500 | 5 | Severe | Severely Worn | Approx. 0.2 |
Data Structure
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| overheat_risk_level | int | Detected potential overheating risk level, ranging from 0 to 5 |
| damage_severity | string | Severity of burn damage (minor, moderate, severe) |
| insulation_condition | string | Condition of the insulating materials (intact, slightly worn, severely worn) |
| anomaly_area_percentage | float | Proportion of the abnormal area in the image, ranging from 0 to 1 |
Compliance Statement
| Item | Content |
|---|---|
| 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 |
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