10.24423/EngTrans.2241.20221116
Detection of the Presence of Rail Corrugation Using Convolutional Neural Network
Maciej TABASZEWSKI
0000-0001-6215-8485
Poznan University of Technology
Poland
Bartosz FIRLIK
0000-0003-3355-5451
Poznan University of Technology
Poland
Rail corrugation is a significant problem not only in heavy-haul freight but also in light rail systems. Over the last years, considerable progress has been made in understanding, measuring and treating corrugation problems also considered a matter of safety.
In the presented research, convolutional neural networks (CNNs) are used to identify the occurrence of rail corrugation in light rail systems. The paper shows that by simultaneously measuring the vibration and the sound pressure, it is possible to identify the rail corrugation with a very small error.
Copyright © The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).
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DOI: 10.24423/EngTrans.2241.20221116