Wheel Polygon Feature Recognition of High-speed Trains Based on Axle-box Acceleration and Wavelet Packet Decomposition

doi:10.3901/JME.2025.14.223

Abstract

Abstract: Efficient wheel polygon detection is of great significance for wheel re-profiling of high-speed trains. A dynamic detection method of wheel polygon features based on wavelet packet decomposition(WPD) of axle-box acceleration is proposed. Firstly, the vehicle-track coupled dynamics model of high-speed train is established, and the axle-box accelerations caused by wheel polygon with different orders and amplitudes are calculated; WPD is used to conduct time-frequency analysis of axle-box accelerations, and the WPD node energy levels is taken as an indicator to quantify the amplitude of wheel polygons; then the mapping between the wheel polygon features and axle-box accelerations features is established by Kriging interpolation model; Finally, the method is verified by direct measurement, the average error of estimated results compared with test results is 10.28%, and for wheels with more serious polygon wear, the average error of estimated of significant order is only 5.68%. To a certain extent, it makes up for the shortage of dynamic detection methods in polygon amplitude quantification, and proposes a new technical way for high-speed train wheel polygon feature detection, which has good engineering value.

Key words: high-speed train, wheel polygonal wear, axle-box acceleration, wavelet packet decomposition, feature recognition, vehicle-track coupled dynamics

CLC Number:

U271

LI Xinyi, LIU Jinan, XIAO Xinbiao, HUANG Zhenxin, LIU Xiaolong, JIN Xuesong. Wheel Polygon Feature Recognition of High-speed Trains Based on Axle-box Acceleration and Wavelet Packet Decomposition[J]. Journal of Mechanical Engineering, 2025, 61(14): 223-232.

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