Abstract
Wheel flat is not only commonly unavoidable surface damage in railway wheels, it can result in possible damage and deterioration incurring high risk of running safety and high maintenance costs. Wheel flat is therefore necessary to be detected at an early stage to minimise safety hazard and maintenance work. This study explores the capacity of the vibration-based detection for high-speed train wheel flatness. A more realistic vehicle-track coupling dynamic model (a dynamic model of vehicle systems of 94 degrees of freedom with wheel flat) considering the dynamic factors of traction transmission, gear transmission and the track geometry irregularities, is established to calculate the dynamic responses of axlebox. In this paper, the proposed method is focus on processing the axle box vertical vibration caused by wheel flat in conventional time and frequency domain, as well as the envelope analysis with a band pass filter. Results demonstrate that the wheel flat can be successfully detected in a more realistic vehicle model, provide an efficient way to the wheel flat detection.
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Acknowledgements
The authors would like to thank the Institute of Railway Research (IRR), and the Centre for Efficiency and Performance Engineering (CEPE) at The University of Huddersfield and the State key laboratory of Traction power at Southwest Jiaotong University for the technical supports.
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Wang, R., Crosbee, D., Beven, A., Wang, Z., Zhen, D. (2020). Vibration-Based Detection of Wheel Flat on a High-Speed Train. In: Ball, A., Gelman, L., Rao, B. (eds) Advances in Asset Management and Condition Monitoring. Smart Innovation, Systems and Technologies, vol 166. Springer, Cham. https://doi.org/10.1007/978-3-030-57745-2_14
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DOI: https://doi.org/10.1007/978-3-030-57745-2_14
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