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基于图像感知的输电线路智能巡检综述OA北大核心CSTPCD

Survey of Intelligent Inspection Based on Image Perception

中文摘要英文摘要

输电线路是电网建设的重要组成部分,定期巡检对于确保输电线路的稳定运行至关重要.文中围绕输电线路智能巡检需求,首先梳理了输电线路不同的巡检方法,介绍了智能巡检中所需的系统框架设备以及智能算法;重点总结了基于传统图像处理和深度学习的智能巡检方法;其次针对输电线路中存在的各种不同故障总结了相关的智能巡检方法,并且通过评价指标进行了对比分析;最后梳理了研究难点,对基于深度学习方法的输电线路巡检发展趋势进行了展望,所提出和总结的输电线路智能巡检方法具有多方面的指导意义.

Transmission line is an essential part of power grid construction.Regular inspection is essential to ensure the stable operation of transmission lines.This paper focuses on the requirements for intelligent inspection of transmission lines.Firstly,different inspection methods of transmission lines are sorted out,and the system framework equipment and intelligent algorithms required in the intelligent inspection are introduced.The intelligent inspection methods based on traditional image processing and deep learning are summarized.Secondly,the relevant intelligent inspection methods are summarized for various faults existing in the transmission lines,and the comparative analysis is carried out through the evaluation index.Finally,the research difficulties are sorted out,and prospects in the development trend of transmission line inspection based on deep learning method are put forward.The intelligent inspection method of transmission line proposed and summarized in this paper is of guiding significance in many fields.

黄新波

西安工程大学电子信息学院,西安 710048||西安市电气设备互联感知与智能诊断重点实验室,西安 710000

输电线路;图像感知;深度学习;智能巡检;故障检测

transmission line;image perception;deep learning;intelligent inspection;fault detection

《高电压技术》 2024 (005)

1826-1841,中插1-中插5 / 21

国家自然科学基金(52307182);金属成形技术与重型装备全国重点实验室(S2208100.W03:2022JQ-568);西安市科技计划项目(22GXFW0041;2022JH-RYFW-0031);陕西省科学技术协会青年人才托举计划项目(20220133).Project supported by National Natural Science Foundation of China(52307182),National Key Laboratory of Metal Forming Technology and Heavy Equipment(S2208100.W03:2022JQ-568),Xi'an Science and Tech-nology Plan Project(22GXFW0041,2022JH-RYFW-0031),Young Talent Fund of Association for Science and Technology in Shaanxi,China(20220133).

10.13336/j.1003-6520.hve.20230553

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