Random vibration analysis of tram-track interaction on a curve due to the polygonal wheel and track irregularity

Abstract

The vibration performance of a tram vehicle running on the curved track is influenced by the speed of the running vehicle, the geometry of the track, the roughness of the wheel and rail, and environmental characteristics. This paper investigates the random vibration analysis of tram-track interaction on a curved track due to the polygonal wheel and track irregularity by the pseudo excitation method (PEM). The dynamic behaviour of tram-track interaction on a curve is modelled using the finite element method (FEM) and multi-body system (MBS). The field tests were carried out to acquire the rail vibration and deformation response, and also measuring the polygonal wheel wear profile to analyse and validate the dynamic behaviour tram-curved track model. The influence of the polygonal wheel on the vibration of tram-curved track coupled system and the wheel-rail contact responses are investigated by considering the wheelset flexibility. The results are illustrated through comparison between with and without the polygonal wheel in terms of time and frequency domain. The numerical results suggest that the wheelset flexibility under the polygonal wheel wear excitation would aggravate the vibration mode of the rail, car-body and axle-box, and also increase the dynamic wheel-rail contact force and creepage.

KEYWORDS:

• Random vibration
• polygonal wheel
• flexible wheelset
• pseudo-excitation method
• wheel-rail impact

Acknowledgements

The present work has been supported by The National Key Research and Development Program of China (2017YFB1201102) and the National Natural Science Foundation of China (51608459, 51778542, 51978586 and U1734207) and Scientific Research Plan of China Railway (K2019G010) and Key Research and Development Projects of Science and Technology Program for Sichuan Province (2019YFG0283) and Open fund of key laboratory of heavy haul railway engineering structure of Ministry of Education (2018JZZ02).

Disclosure statement

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

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [Grant Number 51608459, 51778542, 51978586 and U1734207]; National Key Research and Development Program of China: [Grant Number 2017YFB1201102]; Scientific Research Plan of China Railway: [Grant Number K2019G010]; Key Research and Development Projects of Science and Technology Program for Sichuan Province: [Grant Number 2019YFG0283].