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A reliability-based prognostics framework for railway track management

Chiachío, Juan; Chiachío, Manuel; Prescott, Darren; Andrews, John

Authors

Juan Chiachío

Manuel Chiachío

JOHN ANDREWS john.andrews@nottingham.ac.uk
Professor of Infrastructure Asset Management



Abstract

Railway track geometry deterioration due to traffic loading is a complex problem with important implications in cost and safety. Without appropriate maintenance, track deterioration can lead to severe speed restrictions or disruptions, and in extreme cases, to train derailment. This paper proposes a physics-based reliability-based prognostics framework as a paradigm shift to approach the problem of railway track management. As key contribution, a geo-mechanical elastoplastic model for cyclic ballast settlement is adopted and embedded into a particle filtering algorithm for sequential state estimation and RUL prediction. The suitability of the pro- posed methodology is investigated and discussed through a case study using published data taken from a laboratory simulation of train loading and tamping on ballast carried out at the University of Nottingham (UK).

Citation

Chiachío, J., Chiachío, M., Prescott, D., & Andrews, J. (2017). A reliability-based prognostics framework for railway track management

Conference Name Annual Conference of the Prognostics and Health Management Society, 2017
End Date Oct 5, 2017
Acceptance Date Jun 30, 2017
Publication Date Oct 30, 2017
Deposit Date Dec 12, 2017
Publicly Available Date Dec 12, 2017
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/48676
Publisher URL https://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2017/phmc_17_046.pdf
Related Public URLs https://www.phmsociety.org/events/conference/phm/17/proceedings
https://www.phmsociety.org/node/2376
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
Additional Information Published in: Prognostics and Health Management Society Conference Proceedings 2017, v.8, 046, p. 396-406. ISBN 9781936263264.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0





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