SML-YOLO: a lightweight insulator defect detection algorithm for transmission lines under harsh weather conditions
Guangyang Ren, Haosen Wang · 2026
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Description
Guangyang Ren and Haosen Wang present in this 2026 study a lean defect spotter for power line insulators that works in foul weather. Rain, fog, and dim light blur the cracks inspectors hunt, against cluttered tower backgrounds. Their algorithm trims a current detection framework with a nano backbone, a fused feature pyramid, and a compact head.
The result shrinks the model by about a fifth while lifting accuracy and speed, and it holds up under harsh conditions in tests. The authors aim it at drone inspection, where small computers ride along, cutting manual climbs and outage time. Crews climb less when drones see well. Storm zones gain the most from it.
Catalog record
| CREATOR | Guangyang Ren, Haosen Wang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 62 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |