Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96120
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dc.contributorMainland Development Officeen_US
dc.contributorDepartment of Mechanical Engineeringen_US
dc.creatorHong, Men_US
dc.creatorWang, Qen_US
dc.creatorSu, Zen_US
dc.creatorCheng, Len_US
dc.date.accessioned2022-11-07T03:37:04Z-
dc.date.available2022-11-07T03:37:04Z-
dc.identifier.issn0888-3270en_US
dc.identifier.urihttp://hdl.handle.net/10397/96120-
dc.language.isoenen_US
dc.publisherAcademic Pressen_US
dc.rights© 2013 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2013. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Hong, M., Wang, Q., Su, Z., & Cheng, L. (2014). In situ health monitoring for bogie systems of CRH380 train on Beijing–Shanghai high-speed railway. Mechanical Systems and Signal Processing, 45(2), 378-395 is available at https://doi.org/10.1016/j.ymssp.2013.11.017.en_US
dc.subjectBeijing-Shanghai High-Speed Railwayen_US
dc.subjectCRH380CLen_US
dc.subjectGuided-wave-based damage detectionen_US
dc.subjectHigh-speed train bogie systemen_US
dc.subjectSignal processingen_US
dc.subjectStructural health monitoringen_US
dc.titleIn situ health monitoring for bogie systems of CRH380 train on Beijing–Shanghai high-speed railwayen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage378en_US
dc.identifier.epage395en_US
dc.identifier.volume45en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1016/j.ymssp.2013.11.017en_US
dcterms.abstractBased on the authors' research efforts over the years, an in situ structural health monitoring (SHM) technique taking advantage of guided elastic waves has been developed and deployed via an online diagnosis system. The technique and the system were recently implemented on China's latest high-speed train (CRH380CL) operated on Beijing-Shanghai High-Speed Railway. The system incorporated modularized components including active sensor network, active wave generation, multi-channel data acquisition, signal processing, data fusion, and results presentation. The sensor network, inspired by a new concept - "decentralized standard sensing", was integrated into the bogie frames during the final assembly of CRH380CL, to generate and acquire bogie-guided ultrasonic waves, from which a wide array of signal features were extracted. Fusion of signal features through a diagnostic imaging algorithm led to a graphic illustration of the overall health state of the bogie in a real-time and intuitive manner. The in situ experimentation covered a variety of high-speed train operation events including startup, acceleration/deceleration, full-speed operation (300 km/h), emergency braking, track change, as well as full stop. Mock-up damage affixed to the bogie was identified quantitatively and visualized in images. This in situ testing has demonstrated the feasibility, effectiveness, sensitivity, and reliability of the developed SHM technique and the system towards real-world applications.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMechanical systems and signal processing, 4 Apr. 2014, v. 45, no. 2, p. 378-395en_US
dcterms.isPartOfMechanical systems and signal processingen_US
dcterms.issued2014-04-04-
dc.identifier.scopus2-s2.0-84895060421-
dc.identifier.eissn1096-1216en_US
dc.description.validate202211 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberRGC-B3-1347-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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