电气工程学报 ›› 2021, Vol. 16 ›› Issue (4): 183-188.doi: 10.11985/2021.04.023

• 电力系统 • 上一篇    下一篇

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基于双目视觉技术的特高压输电线路导地线弧垂检测

陈锐锐1(), 王健1(), 蔡峡2(), 陶勇3(), 宫赫4()   

  1. 1.国网甘肃省电力公司兰州供电公司 兰州 730070
    2.国网甘肃省电力公司金昌供电公司 金昌 737100
    3.国网甘肃省电力公司检修公司 兰州 730070
    4.国网辽宁省电力有限公司营口供电公司 营口 115000
  • 收稿日期:2020-12-10 修回日期:2021-05-08 出版日期:2021-12-25 发布日期:2022-02-10
  • 作者简介:陈锐锐,男,1985年生,高级工程师。主要研究方向为智能电网输电技术,传感器应用控制技术和人工智能装备在电力系统中的应用等。E-mail: quewohanyt9@163.com
    王健,男,1979年生,高级工程师。主要研究方向为智能电网输电技术,传感器应用控制技术和人工智能装备在电力系统中的应用等。E-mail: 31581693@qq.com
    蔡峡,男,1979年生,高级工程师。主要研究方向为智能电网输电技术,传感器应用控制技术和人工智能装备在电力系统中的应用等。E-mail: 3090434938@qq.com
    陶勇,男,1974年生,助理工程师。主要研究方向为智能仓储技术,传感器应用控制技术和人工智能装备在电力系统中的应用等。E-mail: 1113119401@qq.com
    宫赫,女,1991年生,硕士。主要研究方向为柔性直流变电技术,逆变器变换控制技术和人工智能装备在电力系统中的应用等。E-mail: 5724647@qq.com

Sag Detection of Conductor and Ground Wire of UHV Transmission Line Based on Binocular Vision Technology

CHEN Ruirui1(), WANG Jian1(), CAI Xia2(), TAO Yong3(), GONG He4()   

  1. 1. Lanzhou Power Supply Company of State Grid Gansu Electric Power Company, Lanzhou 730070
    2. Jinchang Power Supply Company of State Grid Gansu Electric Power Company, Jinchang 737100
    3. State Grid Gansu Electric Power Company Maintenance Company, Lanzhou 730070
    4. Yingkou Power Supply Company of State Grid Liaoning Electric Power Supply Co., Ltd., Yingkou 115000
  • Received:2020-12-10 Revised:2021-05-08 Online:2021-12-25 Published:2022-02-10

摘要:

为提高特高压输电线路导地线弧垂视觉检测能力,实现对导地线跨越交跨距离的实时测量与报警,提出基于双目视觉技术的特高压输电线路导地线弧垂检测方法。构建视觉成像模型,利用融合滤波和信息增强技术进行图像增强,分析人工智能视觉成像特征,基于双目视觉技术,通过图像融合优选控制实现视景重构。采用融合聚类分析方法,通过模糊度辨识和参数融合方法,结合视景重构技术进行特高压输电线路导地线弧垂视景三维重建,采用AR技术进行特高压输电线路导地线弧垂视觉信息处理,得到导地线跨越交跨距离的实时测量与优化处理结果。仿真结果表明,该方法的视景重建能力较好,测量精度较高并且检测耗时较短。

关键词: 双目视觉技术, 特高压, 输电线路, 导地线, 弧垂检测

Abstract:

In order to improve the visual detection ability of the conductor and ground wire sag of UHV transmission line, and realize the real-time measurement and alarm of the cross span distance of the conductor and ground wire, a method based on binocular vision technology for UHV transmission line sag detection is proposed. A visual imaging model is constructed, fusion filtering and information enhancement technology are used for image enhancement, artificial intelligence visual imaging features are analyzed, based on binocular vision technology, visual reconstruction through optimal control of image fusion is realized. Using fusion clustering analysis method, through ambiguity identification and parameter fusion method, combined with the scene reconstruction technology, the three-dimensional reconstruction of the ground wire sag of UHV transmission line is carried out, and AR technology is used to carry out the ground wire sag of UHV transmission line visual information processing, real-time measurement and optimization processing results of the crossing distance of the ground lead. The simulation results show that the method has better visual reconstruction ability, higher measurement accuracy and shorter detection time.

Key words: Binocular vision technology, UHV, transmission lines, ground wire, sag detection

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