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A. Matsumoto, N. Shinoda, H. Tsunashima, Y. Sato, S. Ogata, "Relationship between train vibration and track irregularity for condition-based track maintenance", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 31.13, 2022, doi:10.4203/ccc.1.31.13

Keywords: condition monitoring, track maintenance, IoT device, GPS.

Abstract

Up to now maintenance of railway tracks is conducted mainly based on the track irregularity data measured by track inspection vehicles and/or specialized measurement apparatus. The vibration data of running trains are easy to measure and can be the base of track maintenance, but they have not been used by the basic data of track maintenance because of the shortage of constancy of values. As the special inspection vehicles and apparatus are expensive, it becomes hard to maintain the tracks in regional railway lines and it is keenly desired to develop the economic procedure of track maintenance in local railway lines. Therefore, the authors tried to construct the method for track management based on train vibration data measured by permanently installed small IOT devices on in-service trains with high frequency. After the development of some new data processing methods, especially to obtain accurate positioning data of the trains from GPS speed data, very high constancy of train vibration data has been achieved and verified the relationship between train vibration and track irregularity, which is enough to use track maintenance. In this way, the authors successfully verified the possibility of the “train-vibration-based track maintenance”.

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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: 1 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 31.13 Relationship between train vibration and track irregularity for condition-based track maintenance A. Matsumoto¹, N. Shinoda^1,2, H. Tsunashima¹, Y. Sato², S. Ogata² ¹Nihon University,Japan ² National Traffic Safety & Environment Laboratory, Japan doi:10.4203/ccc.1.31.13 Full Bibliographic Reference for this paper A. Matsumoto, N. Shinoda, H. Tsunashima, Y. Sato, S. Ogata, "Relationship between train vibration and track irregularity for condition-based track maintenance", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 31.13, 2022, doi:10.4203/ccc.1.31.13 Keywords: condition monitoring, track maintenance, IoT device, GPS. Abstract Up to now maintenance of railway tracks is conducted mainly based on the track irregularity data measured by track inspection vehicles and/or specialized measurement apparatus. The vibration data of running trains are easy to measure and can be the base of track maintenance, but they have not been used by the basic data of track maintenance because of the shortage of constancy of values. As the special inspection vehicles and apparatus are expensive, it becomes hard to maintain the tracks in regional railway lines and it is keenly desired to develop the economic procedure of track maintenance in local railway lines. Therefore, the authors tried to construct the method for track management based on train vibration data measured by permanently installed small IOT devices on in-service trains with high frequency. After the development of some new data processing methods, especially to obtain accurate positioning data of the trains from GPS speed data, very high constancy of train vibration data has been achieved and verified the relationship between train vibration and track irregularity, which is enough to use track maintenance. In this way, the authors successfully verified the possibility of the “train-vibration-based track maintenance”. download the full-text of this paper (PDF, 6 pages, 1014 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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