Research on Fault Diagnosis of UR Type Rail Transit DC Circuit Breaker by Sécheron

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Mechanical fault diagnosis of DC circuit breakers is a core component of the online monitoring system for the mechanical state of DC circuit breakers. Based on the Sécheron UR type rail transit DC circuit breaker platform, this paper simulates six typical circuit breaker faults by combining common mechanical faults and the internal structure of the circuit breaker. It captures current, vibration, and stroke signals during fault occurrences and constructs a multi-dimensional feature vector using wavelet packet decomposition and statistical feature extraction. Furthermore, a fault diagnosis model based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) algorithms is proposed. Finally, the model is validated using experimental data to verify its feasibility and accuracy. The results show that the average diagnostic accuracy of this method reaches 95.24%. The research findings provide theoretical support for the reliability maintenance of rail transit power supply systems.

Original languageEnglish
Title of host publication2025 8th International Conference on Energy, Electrical and Power Engineering, CEEPE 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages956-960
Number of pages5
ISBN (Electronic)9798331521844
DOIs
StatePublished - 2025
Event8th International Conference on Energy, Electrical and Power Engineering, CEEPE 2025 - Wuxi, China
Duration: 25 Apr 202527 Apr 2025

Publication series

Name2025 8th International Conference on Energy, Electrical and Power Engineering, CEEPE 2025

Conference

Conference8th International Conference on Energy, Electrical and Power Engineering, CEEPE 2025
Country/TerritoryChina
CityWuxi
Period25/04/2527/04/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • DC circuit breaker
  • Fault diagnosis
  • Feature extraction
  • Hybrid model
  • Rail transit

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