ID-YOLOv7: an efficient method for insulator defect detection in power distribution network
Bojian Chen, Weihao Zhang, Wenbin Wu, Yiran Li, Zhuolei Chen, Chenglong Li · 2024
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Description
Broken insulators on power lines can spark outages, yet spotting tiny flaws in photos of them is hard. Bojian Chen and co-authors built a vision system for that task in a study whose text dates to 2023. Photos from ground-level distribution lines have busier backgrounds and subtler flaws than the aerial shots used for big transmission lines. Standard detectors miss flaws or cry wolf too often in such photos.
Their system, ID-YOLOv7, adds three new parts to a known detector design. One part sharpens edge detail in training images so the model learns flaw shapes. A second part focuses attention across image channels and scales on flaw-like features. A third part merges detail from several scales to rebuild the detector's neck. The goal is fewer missed defects and fewer false alarms for line crews.
Catalog record
| CREATOR | Bojian Chen, Weihao Zhang, Wenbin Wu, Yiran Li, Zhuolei Chen, Chenglong Li |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 57 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |