电子科技2026，Vol.39Issue(5)：65-71,7.DOI:10.16180/j.cnki.issn1007-7820.2026.05.008
基于改进YOLOv7的输电线路绝缘子缺陷检测方法
Transmission Line Insulator Defect Detection Method Based on Improved YOLOv7
摘要
Abstract
As a key device in power systems,insulator defect detection plays a crucial role in ensuring the safe operation of power systems.Existing detection methods rely on traditional image processing technologies and deep learning models,but there are deficiencies in detection accuracy,speed,and robustness.To address the above is-sues,this study proposes an insulator defect detection method based on improved YOLOv7(You Only Look Once ver-sion 7).RepVGG(Re-parameterization Visual Geometry Group)is introduced into the backbone network of YOLOv7 to enhance feature extraction capability,and the DIoU(Distance Intersection over Union)loss function is a-dopted to optimize the regression accuracy of bounding boxes.Experimental results on the public insulator defect de-tection dataset show that the recall rate,mAP@0.5(mean Average Precision)and mAP@0.5:0.95 of the improved YOLOv7 model are increased by 5.8 percentage,0.9 percentage,and 3.4 percentage points respectively,which ver-ifies the effectiveness and superiority of the proposed method,and provides reliable technical support for the safe oper-ation of power systems.关键词
输电线路/绝缘子/YOLOv7/深度学习/目标检测/缺陷检测/RepVGG/损失函数Key words
transmission lines/insulators/YOLOv7/deep learning/target detection/defect detection/RepVGG/loss function分类
信息技术与安全科学引用本文复制引用
陈林,邓松..基于改进YOLOv7的输电线路绝缘子缺陷检测方法[J].电子科技,2026,39(5):65-71,7.基金项目
国家自然科学基金(51977113)National Natural Science Foundation of China(51977113) （51977113）
