A reliability-based prognostics framework for railway track management

Chiachio, Juan and Chiachio, Manuel and Prescott, Darren and Andrews, John (2017) A reliability-based prognostics framework for railway track management. In: Prognostics and Health Management Society Conference Proceedings. PHM Society, Rochester, NY.. ISBN 9781936263264

[img]
Preview
Text (Chiachio-etal-PHMS-2017-A-reliability-based-prognostics-framework-for-railway-track-management)
Chiachio_etal_PHMS_2017_A_reliability_based_prognostics_framework_for_railway_track_management.pdf
Final Published Version
License: Creative Commons Attribution 3.0 logo

Download (413kB)| Preview

    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).