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Estimating railway rail service life: A rail-grid-based approach

Author

Listed:
  • Bai, Lei
  • Liu, Rengkui
  • Wang, Feng
  • Sun, Quanxin
  • Wang, Futian

Abstract

Precise estimation of railway rail service life is of great significance for the efficient use of maintenance and replacement resources and the effective prevention of broken rails. Here, an innovative model for railway rail service life estimation is proposed. A railway line is divided into adjacent segments of the same specific length. Each segment is termed a “rail grid.” Employing the theory of Markov stochastic processes and hazard models, the service life of each rail grid is estimated and the degradation law of each rail grid is customized. The proposed model is verified using five-year rail inspection data for the Longhai Railway. Our evaluation demonstrates that the estimated rail service life is very close to the real rail service life and meets railway management requirements.

Suggested Citation

  • Bai, Lei & Liu, Rengkui & Wang, Feng & Sun, Quanxin & Wang, Futian, 2017. "Estimating railway rail service life: A rail-grid-based approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 54-65.
    • Handle: RePEc:eee:transa:v:105:y:2017:i:c:p:54-65
    DOI: 10.1016/j.tra.2017.08.007
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    References listed on IDEAS

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    1. Lancaster,Tony, 1992. "The Econometric Analysis of Transition Data," Cambridge Books, Cambridge University Press, number 9780521437899, January.
    2. Arne Henningsen & Ott Toomet, 2011. "maxLik: A package for maximum likelihood estimation in R," Computational Statistics, Springer, vol. 26(3), pages 443-458, September.
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    Cited by:

    1. Liying Wang & Mingjie Ding & Boshi Liu & Qingan Qiu, 2025. "Optimizing alternate replacement strategy of k-out-of-n: F systems with common-mode degradation: An application to railway grid," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-24, May.
    2. Bisgaard, Albert Skovgaard & Harrod, Steven & Møller, Jan Kloppenborg & Nielsen, Bo Friis & Rasmussen, Carsten Jørn & Bjørge, Thomas Vatn & Vatn, Jørn, 2025. "A covariate-dependent Markov jump process with application to the propagation of rail defect severity," Reliability Engineering and System Safety, Elsevier, vol. 264(PA).

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