Failure time prediction for vehicle dynamics under performance degradation of dampers and track evolution

Xinliang Dai, Pingbo Wu, Huailong Shi and Hao Sui

Journal of Risk and Reliability, 2024, vol. 238, issue 6, 1256-1270

Abstract: During long-term service, railway vehicles will experience damper performance degradation and track evolution, both have significant effects on the vehicle dynamics performance. This study aims to develop a mathematical model for assessing the failure time of the vehicle system dynamics when considering two random factors. As for the methodology, Wiener processes are used to propose a damper degradation model. Moreover, a continuous-time Markov chain is adopted to describe the state transaction of the track irregularities. In addition, the Monte Carlo method is employed to sample the dynamic responses of the vehicle using stochastic parameters. Finally, the Bayesian theory is utilized to establish the reliability model of the Weibull mixtures under the Dirichlet process prior. The results are obtained through a numerical example: the dampers’ individual differences directly affect effect on the rate of degradation of the vehicle dynamics performance. Furthermore, different indexes positively correlate with each other, mixture models are composed of a small number of components, and Weibull mixtures closely approximate the distribution of the failure time. Compared to other dampers, the anti-yaw dampers have a more significant impact on the vehicle system dynamics. Other results show that each type of damper can adopt a uniform replacement period whereas anti-yaw dampers should be more effectively monitored.

Keywords: Damper performance degradation; reliability; vehicle dynamics; track evolution; Bayesian statistics (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X231202289 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:238:y:2024:i:6:p:1256-1270

DOI: 10.1177/1748006X231202289

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().