Research on identification method of track circuit state of urban rail vehicles based on CEEMDAN-SVM

Meng jie Shao; Congyong Cao; Chen Wang; Jin Kong; Xin Chen

doi:10.1117/12.2668781

16 February 2023 Research on identification method of track circuit state of urban rail vehicles based on CEEMDAN-SVM

Meng jie Shao, Congyong Cao, Chen Wang, Jin Kong, Xin Chen

Proceedings Volume 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022); 1259124 (2023) https://doi.org/10.1117/12.2668781
Event: 6th International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 2022, Guangzhou, China

Abstract

Real time identification of the running state of the track circuit of urban rail vehicles is of great significance to the safe operation of trains. In this paper, a SVM based method for identifying the running state of urban rail vehicle track circuit is proposed. According to the real-time monitoring data of each sensor of the track circuit of the urban rail vehicle, the method of collective empirical mode decomposition is used to extract the features of the voltage signal. Finally, the running state of the track circuit is divided into three states: normal, mild failure and failure.

Citation Download Citation

Meng jie Shao, Congyong Cao, Chen Wang, Jin Kong, and Xin Chen "Research on identification method of track circuit state of urban rail vehicles based on CEEMDAN-SVM", Proc. SPIE 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 1259124 (16 February 2023); https://doi.org/10.1117/12.2668781

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