Autonomous diagnosis of overheating defects in cable accessories based on faster RCNN and mean-shift algorithm

Xiaobing Xu, Chengke Zhou, Wenjun Zhou, Yanqun Liao, Yilong Wei, Jing Yuan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Infrared thermography has been widely used in timely detection of overheating defects in cable accessories. However, the traditional manual diagnosis method is time-consuming and laborious, and it relies too much on expert experience. An autonomous diagnosis method, which is based on the Faster RCNN network and the Mean-Shift algorithm, is proposed in this paper. Firstly, the Faster RCNN network is trained to implement the autonomous identification and positioning of the objects to be diagnosed in images (cable terminations and grounding boxes are included in this paper). Then, the Mean-Shift algorithm is used for image segmentation to rapidly and accurately extract the area of overheating. This is achieved via comparing key regions of the three phase accessories. Next the temperature related characteristic parameters of the overheating region are calculated, and the diagnosis results are obtained in accordance with the relevant cable condition assessment criteria. The proposed method has been applied to test against actual infrared images, and results show that the cable accessories and their overheating regions can be located at different shooting angles and under various background conditions. The research helps reduce the dependence on human efforts and expertise and contributes to improving the practice of condition monitoring.

Original languageEnglish
Title of host publication 2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE)
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Electronic)9781728155111
ISBN (Print)9781728155128
DOIs
Publication statusPublished - 15 Sep 2020

Publication series

Name7th IEEE International Conference on High Voltage Engineering and Application, ICHVE 2020 - Proceedings
PublisherIEEE
ISSN (Print)2381-5043
ISSN (Electronic)2474-3852

Keywords

  • cable accessories
  • faster RCNN
  • infrared image processing
  • mean-shift
  • smart condition diagnosis

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanics of Materials
  • Safety, Risk, Reliability and Quality
  • Electronic, Optical and Magnetic Materials

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