A reliability-based prognostics framework for railway track management

Juan Chiachío-Ruano, Manuel Chiachío-Ruano, Darren Prescott, and John Andrews
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_17_046.pdf402.63 KBSeptember 12, 2017 - 9:36am

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 elasto-plastic 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).

Publication Year: 
2017
Publication Volume: 
8
Publication Control Number: 
046
Submission Keywords: 
Railway Track geometry; Model-based Prognostics; Particle Filtering;
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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