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. 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
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.
王万国, 张晶晶, 韩军, 刘俍, 朱铭武. 基于无人机图像的输电线断股与异物缺陷检测方法[J]. 计算机应用, 2015, 35(8): 2404-2408.
WANG Wanguo, ZHANG Jingjing, HAN Jun, LIU Liang, ZHU Mingwu. Broken strand and foreign body fault detection method for power transmission line based on unmanned aerial vehicle image. Journal of Computer Applications, 2015, 35(8): 2404-2408.
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