Wheel polygonisation growth due to multiple wheelsets/track coupling vibration

Abstract

This present study investigates wheel polygonisation growth on China’s high-speed trains from the perspective of multiple wheelsets/track coupling vibration. Two theoretical models were established: a simplified linear model for polygonal wear trend analysis in the frequency domain, and a detailed nonlinear model for reproducing polygonisation in the time domain. The simulation results suggest that both the amplitude–frequency and phase-frequency characteristics play vital roles in the development of polygonal wear. The rail localised bending resonances between adjacent wheels are the main contributors to the high-order wheel polygonisation. The third and second order rail localised bending modes induce a high amplitude of wear fluctuation at 645 and 400 Hz, respectively, while leading to the phase difference between the wear response and original excitation being closest to 180° at 565 and 330 Hz. Accordingly, wheel polygonisation with frequencies of 572 and 342 Hz achieved the largest wear growth rate. Then, the rail localised bending vibration was captured on-site through a train passing test. And a long-term tracking test of high-speed train was utilised to validate the evolution process of the wheel polygonisation, it was determined that the simulated development of wheel polygonal wear and axlebox acceleration reached agreements with the measured results.

KEYWORDS:

• High-speed train
• wheel/rail wear
• wheel polygonisation
• wheelset/track dynamic model
• rail localised bending mode

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The present work has been supported by the National Natural Science Foundation of China [grant number 51875089], the National Science Foundation for Young Scientists of China [grant number 51805450], the Joint Funds of National Natural Science Foundation of China [grant number U1734201], China Association of Science and Technology Young Talent Support Project [grant number 2019QNRC001], Sichuan Science and Technology Program [grant numbers 2020YJ0075, 2020JDTD0012], the Science and Technology Research Plan of China Railway General Corporation [grant number P2019J002], and the National Key Research and Development Program of China [grant number 2018YFE0201401-01].