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C. Caspersen, M. Skjæveland, T. Ursin, A. Lau, "Towards Predictive Railway Infrastructure Monitoring Using Axle Box Acceleration: A Case Study of the Otta Bridge", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 17.13, 2026, doi:10.4203/ccc.15.17.13

Keywords: axle box acceleration, railway monitoring, predictive maintenance, railway infrastructure, rail maintenance strategy, root mean square, track geometry.

Abstract

This study investigates whether Axle Box Acceleration measurements from passenger trains in regular operaton can be used to identify changes in track and substructure conditions at the Otta Bridge. The motivation is based on the damage event in January 2025, where foundation movement affected the railway infrastructure. The acceleration data are analysed within a common spatial framework by linking measurements to GPS positions. The study applies RMS, FFT, and wavelet analysis to examine local variations in vibration response around the bridge. The results are used to assess whether changes in the acceleration signals can indicate track or substructure degradation. The findings aim to support more continuous and data-driven monitoring of railway infrastructure.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 15 PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 17.13 Towards Predictive Railway Infrastructure Monitoring Using Axle Box Acceleration: A Case Study of the Otta Bridge C. Caspersen, M. Skjæveland, T. Ursin and A. Lau IBM, NTNU, Trondheim, Norway doi:10.4203/ccc.15.17.13 Full Bibliographic Reference for this paper C. Caspersen, M. Skjæveland, T. Ursin, A. Lau, "Towards Predictive Railway Infrastructure Monitoring Using Axle Box Acceleration: A Case Study of the Otta Bridge", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 17.13, 2026, doi:10.4203/ccc.15.17.13 Keywords: axle box acceleration, railway monitoring, predictive maintenance, railway infrastructure, rail maintenance strategy, root mean square, track geometry. Abstract This study investigates whether Axle Box Acceleration measurements from passenger trains in regular operaton can be used to identify changes in track and substructure conditions at the Otta Bridge. The motivation is based on the damage event in January 2025, where foundation movement affected the railway infrastructure. The acceleration data are analysed within a common spatial framework by linking measurements to GPS positions. The study applies RMS, FFT, and wavelet analysis to examine local variations in vibration response around the bridge. The results are used to assess whether changes in the acceleration signals can indicate track or substructure degradation. The findings aim to support more continuous and data-driven monitoring of railway infrastructure. download the full-text of this paper (PDF, 8316 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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