Title
Detection of the Presence of Rail Corrugation Using Convolutional Neural Network
Authors
[ 1 ] Instytut Mechaniki Stosowanej, Wydział Inżynierii Mechanicznej, Politechnika Poznańska | [ 2 ] Instytut Transportu, Wydział Inżynierii Lądowej i Transportu, Politechnika Poznańska | [ P ] employee
Scientific discipline (Law 2.0)
[2.7] Civil engineering, geodesy and transport[2.9] Mechanical engineering
Year of publication
2022
Published in
Article type
scientific article
Publication language
english
Keywords
EN
- corrugation
- vibration and noise
- machine learning
- convolutional networks
Abstract
EN 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.
Pages (from - to)
339 - 353
License type
CC BY-SA (attribution - share alike)
Open Access Mode
open journal
Open Access Text Version
final published version
Full text of article
Access level to full text
public
Ministry points / journal
70
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