发电技术2025，Vol.46Issue(3)：532-540,9.DOI:10.12096/j.2096-4528.pgt.24230
基于无人机巡检的输电线路绝缘子及其异物检测算法
Detection Algorithm for Insulators and Foreign Objects on Transmission Lines Based on Unmanned Aerial Vehicle Inspection
摘要
Abstract
[Objectives]Traditional power grid inspection methods suffer from high labor intensity and low efficiency.Taking Shandong Golden Power Grid as the research object,this study proposes an inspection algorithm using unmanned aerial vehicle(UAV)based on lightweight deep learning network YOLOv5-Mv3 for detecting grid insulators and foreign objects.[Methods]Firstly,a dataset is constructed using images captured by UAVs during power grid inspection and is trained.Then,for the grid insulators and foreign objects,Mobilenetv3 is used to replace CSPDarknet53 as the feature extraction network in order to lighten the YOLOv5-Mv3 model,reducing parameters and computational cost while maintaining accuracy and enabling real-time detection.[Results]The proposed detection algorithm achieves a mean Average Precision of 84.7％and 56.6 frames per second.Compared to Faster RCNN,SSD,and YOLOv4 models,the improved YOLOv5-Mv3 demonstrates higher detection accuracy and faster performance.[Conclusions]The proposed algorithm improves the efficiency of UAV-based power grid inspection and achieves lightweight and high-efficiency effect,fully meeting the requirements for intelligent power grid inspection.关键词
电力系统/人工智能(AI)/电网/无人机/目标检测/输电线路/电力巡检/机器视觉/图像处理Key words
power system/artifical intelligence(AI)/power grid/unmanned aerial vehicle/target detection/transmission line/power inspection/machine vision/image processing分类
动力与电气工程引用本文复制引用
于子涵,王赫鸣,王建凯,朱胜强,孟祥忠..基于无人机巡检的输电线路绝缘子及其异物检测算法[J].发电技术,2025,46(3):532-540,9.基金项目
山东省自然科学基金项目(ZR2022ME194).Project Supported by Shandong Provincial Natural Science Foundation(ZR2022ME194). （ZR2022ME194）
