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Pantograph Catenary Performance Detection of Energy High-Speed Train Based on Machine Vision

Author

Listed:
  • Rong Wang
  • Wan Li
  • Lizhi Tan
  • Haiyu Liu
  • Qiqing Le
  • Songyun Jiang
  • Kevin T. Nguyen
  • Lianhui Li

Abstract

With the rapid development of high-speed rail in China, addressing the issue of safety assurance during the operation of the train is very important. A very important part of a train’s power supply system is the pantograph and catenary system, which consists of a pantograph and a catenary. Failure of the pantograph-catenary system can cause significant damage to the normal operation of the train. The dynamic performance of the pantograph-catheter system must be detected in real time during the operation of the train. This paper is based on the study and analysis of pantograph-catheter dynamic performance parameters and developed a system for real-time detection of pantograph-catheter dynamic performance parameters based on a car visual system. The results are as follows: based on this detection method, the visual error is low and the accuracy is high. The machine-based directional height detection module developed in this paper has a good detection effect and high test accuracy; the arcing detection module designed in this paper can effectively detect the arcing and store the arcing pictures and can display the duration of single arcing and the arcing rate of the section in real-time. The practical application effect is good. The results show that the focal length of the camera lens is 16 mm, and the error of the machine vision system is low. The system designed in this paper may make a great contribution to the operation condition monitoring and fault diagnosis of the pantograph-catenary system of a high-speed train in the future.

Suggested Citation

  • Rong Wang & Wan Li & Lizhi Tan & Haiyu Liu & Qiqing Le & Songyun Jiang & Kevin T. Nguyen & Lianhui Li, 2022. "Pantograph Catenary Performance Detection of Energy High-Speed Train Based on Machine Vision," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, August.
  • Handle: RePEc:hin:jnlmpe:9680545
    DOI: 10.1155/2022/9680545
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