Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Predictive Modelling for Estimation of Railway Track Degradation
Luleå tekniska universitet, Industriell Ekonomi.ORCID iD: 0000-0003-3911-8009
Luleå tekniska universitet, Industriell Ekonomi.ORCID iD: 0000-0002-6479-9101
Responsible organisation
2016 (English)In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadu; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag , 2016, p. 331-347Conference paper, Published paper (Refereed)
Abstract [en]

The degradation processes affecting railway track condition depends both on the resistance of the track and on the stresses subjected to it. Regarding the stresses, both their magnitudes and cycles are of importance when considering the degradation. Furthermore, the stresses have some regularity and variability in the time domain, while the degradation resistance of a track has some spatial regularity as well as variability. In addition, the condition measurements of track may be both irregular and contain measurement errors. Hence, it is challenging to model the condition of track to enable predictions and condition-based maintenance. However, wear prediction models could help to change large parts of the maintenance practice from predominantly corrective to preventive if both the deterministic and the stochastic components of the wear process can be estimated with sufficient accuracy. In this study, one-step-ahead predictions have been used for establishing prognostic models based on repeated measurements of railway track geometry to estimate track wear properties, degradation rates and stochastic behaviour including measurement errors. The prognostic models have then been used for condition assessment and state predictions. Repeated sampling allows for estimations of measurement errors, but the irregular sampling need to be accounted for by interpolation in the time series modelling approach

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag , 2016. p. 331-347
Series
Trafikverkets forskningsportföljer
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Reliability and Maintenance
Research subject
FOI-portföljer, Vidmakthålla
Identifiers
URN: urn:nbn:se:trafikverket:diva-6062DOI: 10.1007/978-3-319-23597-4_24Scopus ID: 2-s2.0-85043755542Local ID: 7501c3d9-b0a9-4f38-9faa-70788a5a4890ISBN: 978-3-319-23596-7 (print)ISBN: 978-3-319-23597-4 (electronic)OAI: oai:DiVA.org:trafikverket-6062DiVA, id: diva2:1744173
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Projects
Samordnad, effektiv planering av järnvägsinfrastrukturunderhåll
Funder
Swedish Transport Administration, TRV 2017/14891Available from: 2016-09-30 Created: 2023-03-17 Last updated: 2023-05-29Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Bergquist, BjarneSöderholm, Peter

Search in DiVA

By author/editor
Bergquist, BjarneSöderholm, Peter
Reliability and Maintenance

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 17 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf