A condition-based maintenance methodology for rails in regional railway networks using evolutionary multiobjective optimization: Case study line Braşov to Zărneşti in Romania

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Abstract

In this paper, we propose a methodology based on signal processing and evolutionary multiobjective optimization to facilitate the maintenance decision making of infra-managers in regional railways. Using a train in operation (with passengers onboard), we capture the condition of the rails using Axle Box Acceleration measurements. Then, using Hilbert-Huang Transform, the locations where the major risks are detected and ssessed with a degradation model. Finally,
evolutionary multiobjective optimization is employed to solve the maintenance decision problem, and to facilitate the visualization of the trade-offs between number of interventions and performance. Real-life measurements from the track from Braşov to Zărneşti in Romania are included to show the methodology.
Original languageEnglish
Title of host publicationProceedings of the IEEEWorld Congress on Computational Intelligence, IEEE WCCI 2018, 2018 Congress on Evolutionary Computation (IEEE CEC 2018)
Subtitle of host publicationRio de Janeiro, Brazil, 8-13 July, 2018
EditorsM. Vellasco, P. Estevez, Gary G. Yen
PublisherIEEE
Number of pages7
DOIs
Publication statusPublished - 2018
EventWorld Congress on Computational Intelligence, 2018 Congress on Evolutionary - Rio de Janeiro, Brazil
Duration: 8 Jul 201813 Jul 2018
http://www.ecomp.poli.br/~wcci2018/

Conference

ConferenceWorld Congress on Computational Intelligence, 2018 Congress on Evolutionary
Abbreviated titleWCCI 2018, CEC 2018
CountryBrazil
CityRio de Janeiro
Period8/07/1813/07/18
Internet address

Keywords

  • Multiobjective optimization
  • acceleration measurements
  • Railway Engineering
  • ARMOEA
  • KPIs

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