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 - Railway Engineering)

Siwarak Unsiwilai (TU Delft - Railway Engineering)

Yuanchen Zeng (TU Delft - Railway Engineering)

Chen Shen (TU Delft - Railway Engineering)

Jurjen Hendriks (TU Delft - Railway Engineering)

Jan Moraal (TU Delft - Railway Engineering)

Arjen Zoeteman (ProRail)

Alfredo Nunez (TU Delft - Railway Engineering)

Rolf Dollevoet (TU Delft - Railway Engineering)

Zili Li (TU Delft - Railway Engineering)

Research Group
Railway Engineering
DOI related publication
https://doi.org/10.1007/978-3-031-88974-5_42 Final published version
More Info
expand_more
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
Downloads counter
374
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

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.