Condition monitoring of railway transition zones using acceleration measurements on multiple axle boxes

Case studies in the Netherlands, Sweden, and Norway

Conference Paper (2024)
Author(s)

Li Wang (TU Delft - Civil Engineering & Geosciences)

Siwarak Unsiwilai (TU Delft - Civil Engineering & Geosciences)

Yuanchen Zeng (TU Delft - Civil Engineering & Geosciences)

Chen Shen (TU Delft - Civil Engineering & Geosciences)

Jurjen Hendriks (TU Delft - Civil Engineering & Geosciences)

Jan Moraal (TU Delft - Civil Engineering & Geosciences)

Arjen Zoeteman (ProRail)

Alfredo Nunez (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/10.1007/978-3-031-88974-5_42 Final published version
More Info
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Publication Year
2024
Language
English
Related content
Research Group
Railway Engineering
Pages (from-to)
290-296
Publisher
Springer
ISBN (print)
978-3-031-88973-8
ISBN (electronic)
978-3-031-88974-5
Event
The 10th Transport Research Arena Conference 2024 (2024-04-15 - 2024-04-18), The Royal Dublin Society (RDS), Dublin, Ireland
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Abstract

Railway transition zones connecting conventional embankments and rigid struc-tures, such as bridges and tunnels, usually degrade much faster than other railway sections. Efficient health condition monitoring of transition zones is important for preventative track maintenance. In this paper, a methodology for monitoring rail-way transition zones using acceleration measurements on multiple axle boxes (multi-ABA) of a passing train is presented. To showcase its capability, the measurements in the Netherlands, Sweden, and Norway are analyzed and dis-cussed. It is found that different bridges and transition zones exhibit unique char-acteristics including dominant wavelengths and energy distribution. Based on these unique characteristics, the geometry and support conditions at different lo-cations of a transition zone can be evaluated. Higher train speed makes the char-acteristics more pronounced. The results demonstrate that the multi-ABA meas-urement has the potential to evaluate and thus monitor the health conditions of various transition zones.