PSI - Issue 54

Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com ScienceDirect

www.elsevier.com/locate/procedia

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Procedia Structural Integrity 54 (2024) 545–552

International Conference on Structural Integrity 2023 (ICSI 2023) Surface defect detection systems for railway components Francisco Afonso a, *, Pedro Sousa a , Susana Aguiar a , João Nunes a , Nuno Viriato a ,

Frederico P. Direito a , Paulo Tavares a , Pedro Moreira a a INEGI, Campus da FEUP, Rua Dr. Roberto Frias 400, Porto 4200-465, Portugal

© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0 ) Peer-review under responsibility of the scientific committee of the ICSI 2023 organizers Abstract Defects located both in railway tracks and train wheels can become critical to the well-functioning of the railway system, going as far as to halt the movement of trains or require manual intervention to avoid accidents. In that regard, as part of the Ferrovia 4.0 project which aims to improve Portuguese railways, two systems were developed to detect surface level defects in these areas. Both systems implement 3D laser line sensors to measure profiles; these sensors are equipped with cameras, a laser and work using the principle of triangulation. An algorithm was developed, for each system, allowing the implementation of different metrics and their respective tolerances, warning the technician when a defect is detected and, in the case of the railway track defect detection system, the presence of defects is also transmitted to a maintenance platform. Both algorithms compare the profiles of railway tracks and train wheels to their respective defect free templates, acquired beforehand. While the railway tracks system is to be implemented on a fully assembled train carriage, the wheel system was developed for application in repair shop environment. Both systems are able to successfully compare the profiles captured during trials to their respective templates, warning the technician every time a profile went outside the established tolerances which, in turn, can easily be adjusted, and successfully communicated with the maintenance platform when a defect was detected. This work was developed in the s cope of the project FERROVIA 4.0, nº 46111 which has received funding from “ANI - Agência Nacional de Inovação, S.A” through the programme “Mobilizador COPROMOÇÃO_PT2020”. © 2023 The Authors, Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the ICSI 2023 organizers Keywords: Laser Sensor; Defect Detection; Railway

E-mail address: fafonso@inegi.up.pt

2452-3216 © 2023 The Authors, Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the ICSI 2023 organizers

2452-3216 © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the ICSI 2023 organizers 10.1016/j.prostr.2024.01.117