Acceleration sensor technology for rail track asset condition monitoring

Klaus Känsälä*, Seppo Rantala, Osmo Kauppila, Pekka Leviäkangas

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    7 Citations (Scopus)

    Abstract

    In the rail traffic industry, the utilisation of inexpensive real-time sensors and the industrial internet of things for proactive asset management is a relatively new concept with great potential. As railways are one of the longest-lasting infrastructure assets, even marginal efficiency and cost gains have a significant impact on the life-cycle cost. This paper shows how wireless three-dimensional acceleration sensor technology can be applied to monitor track condition. The data collection was carried out in October 2016 on a railway line operated by Finnish Railways. In the test, a sensor was attached to a train unit and the acceleration of the train on a track segment was repeatedly measured at variable speeds. The collected data set was enhanced using map-matching and Bayesian filtering in order to improve the Global Positioning System location accuracy of the data. The filtered acceleration signals were analysed, and detected anomalies were compared against known parameters such as bridges and switches. The results of the testing support the feasibility of the concept. Finally, the implications of the concept regarding proactive asset management of track networks and statistical process control-based monitoring of tracks’ condition are discussed.

    Original languageEnglish
    Pages (from-to)32-40
    Number of pages9
    JournalProceedings of Institution of Civil Engineers: Management, Procurement and Law
    Volume171
    Issue number1
    DOIs
    Publication statusPublished - 5 Feb 2018
    MoE publication typeA1 Journal article-refereed

    Funding

    The authors would like to acknowledge the VTT Technical Research Centre of Finland for supporting this research. The Finnish Transport Agency and VR Group Ltd (Finnish Railways) are also acknowledged for collaboration and facilitation of this research. Map data © OpenStreetMap contributors and Google. Style licensed under a Attribution-ShareAlike 2.0 Generic license (CC-BY-SA 2.0) by OpenRailwayMap and OpenStreetMap.

    Keywords

    • Information technology/maintenance & inspection/railway systems

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