电气技术2025，Vol.26Issue(9)：62-68,78,8.
基于深度学习的架空输电线路绝缘子识别方法研究
Research on deep learning based insulator recognition method for overhead transmission lines
宋欣杰 1金一鸣1
作者信息
- 1. 国网浙江省电力有限公司德清县供电公司,浙江 湖州 313200
- 折叠
摘要
Abstract
Insulators with defects such as breakage,cracks and drops affect the stability of power system operation and reliability of power supply.Thus this paper proposes a deep learning based insulator recognition method for overhead transmission lines to improve the recognition accuracy.The coordinate attention(CA)mechanism is introduced into you only look once(YOLO)v7-tiny model and the convolution kernel of 3×3 with a step size of 1 is replaced by the deformable convolutional network(DCN)v2.The intersection over union(IoU)value of loss function is replaced by the normalized Wasserstein distance(NWD)to improve the insulator recognition capability in complex and occluded environments.The experimental results show that the improved YOLOv7-tiny model can effectively enhance the insulator recognition accuracy by improving the mean average precision(mAP)by 8.6%,4.7%,0.8%,and 3.4%compared with faster region convolutional neural network(Faster R-CNN),YOLOv5s,YOLOv7,and the original YOLOv7-tiny,respectively.关键词
深度学习/架空输电线路/绝缘子识别Key words
deep learning/overhead transmission lines/insulator recognition引用本文复制引用
宋欣杰,金一鸣..基于深度学习的架空输电线路绝缘子识别方法研究[J].电气技术,2025,26(9):62-68,78,8.
