Railway track geometry deterioration due to traffic loadingis a complex problem with important implications in costand safety. Without appropriate maintenance, track deteriorationcan lead to severe speed restrictions or disruptions, andin extreme cases, to train derailment. This paper proposesa physics-based reliability-based prognostics framework asa paradigm shift to approach the problem of railway trackmanagement. As key contribution, a geo-mechanical elastoplasticmodel for cyclic ballast settlement is adopted and embeddedinto a particle filtering algorithm for sequential stateestimation and RUL prediction. The suitability of the proposedmethodology is investigated and discussed through acase study using published data taken from a laboratory simulationof train loading and tamping on ballast carried out atthe University of Nottingham (UK).
CITATION STYLE
Chiachio, J., Chiachio, M., Prescott, D., & Andrews, J. (2017). A reliability-based prognostics framework for railway track management. In Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM (pp. 396–406). Prognostics and Health Management Society. https://doi.org/10.36001/phmconf.2017.v9i1.2455
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