基于深度学习技术的无人机输电线路元件检测系统  

UAV transmission line component detection system based on deep learning technology

作　　者：李欣哲 赵强 乐天达 章志鸿 周岐跃 LI Xinzhe;ZHAO Qiang;YUE Tianda;ZHANG Zhihong;ZHOU Qiyue(Wuxi Guangying Electric Power Design Co.,Ltd.,Wuxi 214000,China)

机构地区：[1]无锡市广盈电力设计有限公司,江苏无锡214000

出　　处：《中国高新科技》2025年第1期115-117,共3页

摘　　要：输电线路作为电力系统的重要组成部分,其安全运行直接关系社会经济的稳定发展和居民生活的正常进行。文章介绍了一种结合无人机与深度学习技术的输电线路元件检测系统。该系统能够自动识别和定位输电线路上的潜在故障。它利用无人机搭载高精度传感器进行数据采集,结合深度学习模型进行数据处理和分析,有效提高了巡检的效率和准确性。Transmission line as an important part of the power system,its safe operation is directly related to the stable development of national economy and the normal progress of social life.This paper introduces a transmission line component detection system combining UAV and deep learning technology,which can automatically identify and locate potential faults on transmission lines.The system uses UAV to carry high-precision sensor for data acquisition,combined with deep learning model for data processing and analysis,effectively improving the efficiency and accuracy of inspection.

关 键 词：无人机 深度学习 输电线路 元件检测 智能巡检 

分 类 号：TM75[电气工程—电力系统及自动化]