Real-time techniques for fault detection on railway door systems

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dc.contributor.authorShimizu, Minoru
dc.contributor.authorPerinpanayagam, Suresh
dc.contributor.authorNamoano, Bernadin
dc.date.accessioned2022-08-22T15:30:28Z
dc.date.available2022-08-22T15:30:28Z
dc.date.issued2022-08-10
dc.description.abstractThis paper focuses on real-time techniques for fault detection in railway assets through large real-world datasets. It aims to investigate data mining methods to detect faulty behaviour in time series data. A fault detection on railway door systems is carried out using motor current and encoder signal. The door data highlighted start-stop characteristics, with discontinuities in the data. This paper presents a successful fault detection technique, which is a feature-based machine learning method that requires several steps for time-series data processing, such as signal segmentation and the extraction of features. Principal Component Analysis (PCA) is applied to reduce the dimensionality of the extracted feature set and generate condition indicators. Then, the k-means algorithm is employed to separate normal and abnormal behaviour. This is followed by an evaluation of the proposed method and discussion about current challenges and prognosis possibility.en_UK
dc.identifier.citationShimizu M, Perinpanayagam S, Namoano B. (2022) Real-time techniques for fault detection on railway door systems. In: 2022 IEEE Aerospace Conference, 5-12 March 2022, Big Sky, MT, USAen_UK
dc.identifier.eisbn978-1-6654-3760-8
dc.identifier.isbn978-1-6654-3761-5
dc.identifier.issn1095-323X
dc.identifier.urihttps://doi.org/10.1109/AERO53065.2022.9843627
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18342
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rights© Cranfield University, 2015. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.titleReal-time techniques for fault detection on railway door systemsen_UK
dc.typeConference paperen_UK

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