Research on wheel polygon order recognition technology based on spatial spectrum

Yu-lun Zhao; Xiao-jie Sun; Zhen-bang Li; Jin Luo

doi:10.1117/12.2689604

7 September 2023 Research on wheel polygon order recognition technology based on spatial spectrum

Yu-lun Zhao, Xiao-jie Sun, Zhen-bang Li, Jin Luo

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127901U (2023) https://doi.org/10.1117/12.2689604
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

As rail vehicles cover more mileage and run at higher speeds, the problem of abnormal wear between the wheel and rail becomes increasingly prominent. Identifying wheel polygons is a crucial aspect of tackling this issue. In this study, acceleration signals are collected using the wheel rotation angle as the reference instead of time, and signal processing is carried out using the spatial spectrum Fourier transform. The results demonstrate that the Fourier transform based on the spatial spectrum can accurately identify the abnormal frequency of polygon distribution. This method solves the problem of polygon order recognition under changing train speeds and maintains good recognition accuracy. Simulation results show that the recognition accuracy under different speed segments is higher than 95%, and polygon order recognition can be conducted under different working conditions with robustness.

Citation Download Citation

Yu-lun Zhao, Xiao-jie Sun, Zhen-bang Li, and Jin Luo "Research on wheel polygon order recognition technology based on spatial spectrum", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127901U (7 September 2023); https://doi.org/10.1117/12.2689604

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