A condition-based maintenance methodology for rails in regional railway networks using evolutionary multiobjective optimization

Case study line Braşov to Zărneşti in Romania

Conference Paper (2018)
Author(s)

Alfredo Nunez (TU Delft - Civil Engineering & Geosciences)

Ali Jamshidi (TU Delft - Civil Engineering & Geosciences)

Hongrui Wang (TU Delft - Civil Engineering & Geosciences)

Jurjen Hendriks (TU Delft - Civil Engineering & Geosciences)

Ivan Ramirez Fonseca (TU Delft - Civil Engineering & Geosciences)

Jan Moraal (TU Delft - Civil Engineering & Geosciences)

Rolf Dollevoet (TU Delft - Civil Engineering & Geosciences)

Zili Li (TU Delft - Civil Engineering & Geosciences)

Research Group
Railway Engineering
DOI related publication
https://doi.org/10.1109/CEC.2018.8477842 Final published version
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Publication Year
2018
Language
English
Research Group
Railway Engineering
Event
World Congress on Computational Intelligence, 2018 Congress on Evolutionary (2018-07-08 - 2018-07-13), Rio de Janeiro, Brazil
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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.

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