计算机应用 ›› 2015, Vol. 35 ›› Issue (8): 2404-2408.DOI: 10.11772/j.issn.1001-9081.2015.08.2404

• 行业与领域应用 • 上一篇    下一篇

基于无人机图像的输电线断股与异物缺陷检测方法

王万国1,2, 张晶晶1,2, 韩军3, 刘俍1,2, 朱铭武3   

  1. 1. 国网山东省电力公司电力科学研究院 国家电网公司电力机器人技术实验室, 济南 250002;
    2. 山东鲁能智能技术有限公司, 济南 250101;
    3. 上海大学 通信与信息工程学院, 上海 200444
  • 收稿日期:2015-03-12 修回日期:2015-05-08 出版日期:2015-08-10 发布日期:2015-08-14
  • 通讯作者: 韩军(1965-),男,河南三门峡人,高级工程师,博士,主要研究方向:图像处理、视频修复,2254285987@qq.com
  • 作者简介:王万国(1984-),男,山东柳城人,中级工程师,硕士,主要研究方向:基于数字图像的变电站和输电线路设备识别、目标跟踪、图像去雾; 张晶晶(1984-),男,浙江金华人,中级工程师,硕士,主要研究方向:图像处理、人工智能、无人机巡检; 刘俍(1984-),男,山东济南人,工程师,硕士,主要研究方向:无人机巡检、计算机软件; 朱铭武(1988-),男,安徽宣城人,硕士研究生,主要研究方向:数字图像处理。
  • 基金资助:

    2014年国家电网发展项目(169)。

Broken strand and foreign body fault detection method for power transmission line based on unmanned aerial vehicle image

WANG Wanguo1,2, ZHANG Jingjing1,2, HAN Jun3, LIU Liang1,2, ZHU Mingwu3   

  1. 1. Electric Power Robotics Laboratory of State Grid Corporation of China, Shandong Electric Power Research Institute, Jinan Shandong 250002, China;
    2. Shandong Luneng Intelligence Technology Company Limited, Jinan Shandong 250101, China;
    3. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
  • Received:2015-03-12 Revised:2015-05-08 Online:2015-08-10 Published:2015-08-14

摘要:

为提高无人机(UAV)巡检输电线路的效率,提出一种基于线结构感知的输电线断股与异物缺陷的检测方法。由于无人机巡检的图像受背景纹理及光线影响较大,采用能检测线宽度的水平与垂直方向的梯度算子提取巡检图像上的线对象,进而研究感知定律中的共线性、近似性、连续性的计算,将断续线段连接成长的线段,通过长线段的平行性计算,识别出输电线路结构中显著的平行导线组。为识别导线上安装的防振锤与间隔棒连接部件,提出一种基于局部轮廓特征的形状部件识别方法。在识别出这些连接部件的基础上,对导线进行分段分析,计算分段导线的宽度变化、灰度相似度来检测导线上的断股与异物缺陷。通过对无人机巡检采集的输电线路图像的测试,验证了这种方法在复杂的背景条件下能有效地检测导线上断股与附着异物缺陷。

关键词: 导线断股, 导线附着异物, 感知平行性, 局部轮廓特征, 缺陷检测

Abstract:

In order to improve the efficiency of power transmission line inspection by Unmanned Aerial Vehicle (UAV), a new method was proposed for detecting broken transmission lines and defects of foreign body based on the perception of line structure. The transmission line image acquired by UAV was easily influenced by the background texture and light, the gradient operators of horizontal and vertical direction which can be used to detect the line width were used to extract line objects in the inspection image. The study on calculation of gestalt perception of similarity, continuity and colinearity connected the intermittent wires into continuous wires. Then the parallel wire groups were further determined through the calculation of parallel relationship between wires. In order to reduce the detection error rate, spacers and stockbridge dampers of wires were recognized based on a local contour feature. Finally, the width change and gray similarity of segmented conductor wire were calculated to detect the broken part of wire and foreign object defect. The experimental results show that the proposed method can detect broken wire strand and foreign object defect efficiently under complicated backgrounds from the transmission line of UAV images.

Key words: broken conductor strand, wire attached foreign body, perception of parallelism, local contour feature, defect detection

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