{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:31:49Z","timestamp":1779064309434,"version":"3.51.4"},"reference-count":41,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Junta de Andaluc\u00eda, Andaluc\u00eda","award":["US-1381456"],"award-info":[{"award-number":["US-1381456"]}]},{"name":"Junta de Andaluc\u00eda, Andaluc\u00eda","award":["PID2022-137748OB-C32"],"award-info":[{"award-number":["PID2022-137748OB-C32"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033\/FEDER, EU","award":["US-1381456"],"award-info":[{"award-number":["US-1381456"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033\/FEDER, EU","award":["PID2022-137748OB-C32"],"award-info":[{"award-number":["PID2022-137748OB-C32"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a deep learning approach for predicting rail corrugation based on on-board rolling-stock vertical acceleration and forward velocity measurements using One-Dimensional Convolutional Neural Networks (CNN-1D). The model\u2019s performance is examined in a 1:10 scale railway system at two different forward velocities. During both the training and test stages, the CNN-1D produced results with mean absolute percentage errors of less than 5% for both forward velocities, confirming its ability to reproduce the corrugation profile based on real-time acceleration and forward velocity measurements. Moreover, by using a Gradient-weighted Class Activation Mapping (Grad-CAM) technique, it is shown that the CNN-1D can distinguish various regions, including the transition from damaged to undamaged regions and one-sided or two-sided corrugated regions, while predicting corrugation. In summary, the results of this study reveal the potential of data-driven techniques such as CNN-1D in predicting rails\u2019 corrugation using online data from the dynamics of the rolling-stock, which can lead to more reliable and efficient maintenance and repair of railways.<\/jats:p>","DOI":"10.3390\/s24144627","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T15:15:19Z","timestamp":1721229319000},"page":"4627","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Predicting Rail Corrugation Based on Convolutional Neural Networks Using Vehicle\u2019s Acceleration Measurements"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2042-6645","authenticated-orcid":false,"given":"Masoud","family":"Haghbin","sequence":"first","affiliation":[{"name":"Department of Structural Mechanics and Hydraulic Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada (UGR), 18001 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1243-8694","authenticated-orcid":false,"given":"Juan","family":"Chiach\u00edo","sequence":"additional","affiliation":[{"name":"Department of Structural Mechanics and Hydraulic Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada (UGR), 18001 Granada, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6003-622X","authenticated-orcid":false,"given":"Sergio","family":"Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Department of Materials and Transportation Engineering, Escuela T\u00e9cnica Superior de Ingenier\u00eda, University of Seville, 41092 Seville, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose Luis","family":"Escalona Franco","sequence":"additional","affiliation":[{"name":"Department of Materials and Transportation Engineering, Escuela T\u00e9cnica Superior de Ingenier\u00eda, University of Seville, 41092 Seville, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio J.","family":"Guill\u00e9n","sequence":"additional","affiliation":[{"name":"Department of Management, Complutense University of Madrid, 28040 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2027-7096","authenticated-orcid":false,"given":"Adolfo","family":"Crespo Marquez","sequence":"additional","affiliation":[{"name":"Department of Industrial Management, Escuela T\u00e9cnica Superior de Ingenier\u00eda, University of Seville, 41092 Seville, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6235-5304","authenticated-orcid":false,"given":"Sergio","family":"Cantero-Chinchilla","sequence":"additional","affiliation":[{"name":"School of Electrical, Electronic and Mechanical Engineering, University of Bristol, Bristol BS8 1TR, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1243\/09544097JRRT264","article-title":"Rail corrugation: Characteristics, causes, and treatments","volume":"223","author":"Grassie","year":"2009","journal-title":"Proc. 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