@inproceedings{9cf74b3297a04ea882cdf52d70a58ed8,
title = "Intelligent Optical Fibre Sensing Networks Facilitate Shift to Predictive Maintenance in Railway Systems",
abstract = "This paper depicts an optical fibre sensing network based railway health condition monitoring system that can facilitate predictive maintenance in railways. Machine learning is applied to develop learning models that can be used to detect and identify different types of track defects such as rail corrugations, dipped weld joints and rail crossings.",
keywords = "dipped weld joints, fibre Bragg grating, machine learning, optical fiber sensing network, predictive railway maintenance, rail corrugation",
author = "Tam, {Hwa Yaw} and Lee, {Kang Kuen} and Liu, {Shun Yee} and Cho, {Lok Hin} and Cheng, {Kei Chun}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 2018 International Conference on Intelligent Rail Transportation, ICIRT 2018 ; Conference date: 12-12-2018 Through 14-12-2018",
year = "2019",
month = feb,
day = "13",
doi = "10.1109/ICIRT.2018.8641602",
language = "English",
series = "2018 International Conference on Intelligent Rail Transportation, ICIRT 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 International Conference on Intelligent Rail Transportation, ICIRT 2018",
}