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With the development of unmanned aerial vehicle (UAV) technology, visible images are playing an important role in the maintenance of power systems. To achieve the shed breakage evaluation of composite insulators by UAV visible images, an intelligent fault assessment method is proposed. First, the composite insulators in visible light images are identified by Faster-RCNN. After image preprocessing, the image is enhanced and the noise is removed. Then, a canny operator is used to extract the edge of the sheds. An Improved Randomized Hough Transform (IRHT) is used to detect the ellipses in the edge image. The parameters of the detected ellipse, length of major axes and minor axes, center coordinates and deflection angle of major axes, are used to realize the segmentation of the composite insulator. Finally, the number of pixel points in the ellipse and the distance between the points and the ellipse boundary are used to judge whether there are breakage or cracks on the sheds. The area ratio of the breakage to the whole shed is calculated based on the number of pixel points inside the broken area. This method can be realized without a large amount of training dataset of the specific fault type and provides a technical basis for the online fault assessment of a composite insulator on overhead transmission lines.


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Intelligent Breakage Assessment of Composite Insulators on Overhead Transmission Lines by Ellipse Detection Based on IRHT

Show Author's information Zhikang Yuan1Linxuan He2( )Shaohe Wang3Youping Tu2Zhaojing Li2Cong Wang2Fan Li4
College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
State Grid Zhejiang Electric Power Research Institute, Hangzhou 310014, China
State Grid Jiangxi Electric Power Research Institute, Nanchang 330000, China

Abstract

With the development of unmanned aerial vehicle (UAV) technology, visible images are playing an important role in the maintenance of power systems. To achieve the shed breakage evaluation of composite insulators by UAV visible images, an intelligent fault assessment method is proposed. First, the composite insulators in visible light images are identified by Faster-RCNN. After image preprocessing, the image is enhanced and the noise is removed. Then, a canny operator is used to extract the edge of the sheds. An Improved Randomized Hough Transform (IRHT) is used to detect the ellipses in the edge image. The parameters of the detected ellipse, length of major axes and minor axes, center coordinates and deflection angle of major axes, are used to realize the segmentation of the composite insulator. Finally, the number of pixel points in the ellipse and the distance between the points and the ellipse boundary are used to judge whether there are breakage or cracks on the sheds. The area ratio of the breakage to the whole shed is calculated based on the number of pixel points inside the broken area. This method can be realized without a large amount of training dataset of the specific fault type and provides a technical basis for the online fault assessment of a composite insulator on overhead transmission lines.

Keywords: composite insulator, Breakage assessment, ellipse detection, Improved Randomized Hough Transform (IRHT)

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Received: 24 April 2021
Revised: 06 August 2021
Accepted: 29 August 2021
Published: 06 May 2022
Issue date: September 2023

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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