A reliability-based prognostics framework for railway track management

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...

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Main Authors: Chiachío, Juan, Chiachío, Manuel, Prescott, Darren, Andrews, John
Format: Conference or Workshop Item
Published: 2017
Online Access:https://eprints.nottingham.ac.uk/48676/
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author Chiachío, Juan
Chiachío, Manuel
Prescott, Darren
Andrews, John
author_facet Chiachío, Juan
Chiachío, Manuel
Prescott, Darren
Andrews, John
author_sort Chiachío, Juan
building Nottingham Research Data Repository
collection Online Access
description 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).
first_indexed 2025-11-14T20:09:57Z
format Conference or Workshop Item
id nottingham-48676
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T20:09:57Z
publishDate 2017
recordtype eprints
repository_type Digital Repository
spelling nottingham-486762020-05-04T19:15:03Z https://eprints.nottingham.ac.uk/48676/ A reliability-based prognostics framework for railway track management Chiachío, Juan Chiachío, Manuel Prescott, Darren Andrews, John 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). 2017-10-30 Conference or Workshop Item PeerReviewed Chiachío, Juan, Chiachío, Manuel, Prescott, Darren and Andrews, John (2017) A reliability-based prognostics framework for railway track management. In: Annual Conference of the Prognostics and Health Management Society, 2017, 2-5 October 2017, St. Petersburg, Florida, USA. https://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2017/phmc_17_046.pdf
spellingShingle Chiachío, Juan
Chiachío, Manuel
Prescott, Darren
Andrews, John
A reliability-based prognostics framework for railway track management
title A reliability-based prognostics framework for railway track management
title_full A reliability-based prognostics framework for railway track management
title_fullStr A reliability-based prognostics framework for railway track management
title_full_unstemmed A reliability-based prognostics framework for railway track management
title_short A reliability-based prognostics framework for railway track management
title_sort reliability-based prognostics framework for railway track management
url https://eprints.nottingham.ac.uk/48676/
https://eprints.nottingham.ac.uk/48676/