南方电网技术2023，Vol.17Issue(12)：127-134,8.DOI:10.13648/j.cnki.issn1674-0629.2023.12.015
基于改进YOLOv7的实时输电导线缺陷检测方法
Real-Time Transmission Wire Defect Detection Method Based on Improved YOLOv7
摘要
Abstract
Transmission wire plays an important part of the power system,and defects in transmission wire will affect the operation of the power system.A transmission wire defect detection method based on the improved YOLOv7 algorithm is proposed.First,a method of automatically expanding the data set is proposed in this paper,which can use a small number of pictures to establish a data set of transmission wire defects.Then,a lightweight self-attention backbone network is proposed,which replaces the YOLOv7's backbone network,and uses the BiFPN to perform feature fusions.The experimental results show that the improved YOLOv7 algorithm proposed improves the accuracy from the original 89.4%to 97.5%.At the same time,the detection speed is increased by about 60.49%,and the FPS is improved from the original 52.36 frames to 84.03 frames;real-time detection of transmission lines can be achieved,which reduces the misdetection and omission rate of transmission wire defects,as well as improves the detection speed and enhances the inspection efficiency.关键词
输电线路/缺陷检测/YOLOv7算法/自注意力机制/实时检测Key words
transmission line/defect detection/YOLOv7 algorithm/self-attention mechanism/real-time detection分类
信息技术与安全科学引用本文复制引用
王宇博,尚军利,张烨,刘建勇,杨雷,李博涛..基于改进YOLOv7的实时输电导线缺陷检测方法[J].南方电网技术,2023,17(12):127-134,8.基金项目
陕西省自然科学基础研究计划资助项目(2022JQ-568) （2022JQ-568）
陕西省教育厅科研计划资助项目(21JK0661) （21JK0661）
陕西省渭南市供电公司2022科技项目(5226WN220001). Supported by the Natural Science Basis Research Program of Shaanxi Province of China(2022JQ-568) （5226WN220001）
the Scientific Research Program of Shaanxi Provincial Education Department(21JK0661) （21JK0661）
the Science and Technology Project of State Grid Weinan Power Supply Company(5226WN220001). （5226WN220001）
