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dc.contributor.authorHazra, Budhaditya
dc.contributor.authorNarasimhan, Sriram
dc.date.accessioned2018-03-05 15:07:44 (GMT)
dc.date.available2018-03-05 15:07:44 (GMT)
dc.date.issued2016
dc.identifier.urihttp://dx.doi.org/10.1016/j.proeng.2016.05.023
dc.identifier.urihttp://hdl.handle.net/10012/13028
dc.descriptionThe final publication is available at Elsevier via http://dx.doi.org/10.1016/j.proeng.2016.05.023 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.description.abstractThis paper presents a novel fault-detection method for gearbox vibration signatures using synchro-squeezing transform (SST). Premised upon the concept of time-frequency (TF) reassignment, SST provides a sharp representation of signals in TF plane compared to many popular TF methods. Additionally, it can also extract the individual components, called intrinsic mode functions or IMFs, of a non-stationary multi-component signal, akin to empirical mode decomposition. The rich mathematical structure based on continuous wavelet transform makes SST a promising candidate for gearbox diagnosis. This work utilizes the decomposing power of SST to extract the IMFs from gearbox signals. For robust detection of faults in gear-motors, a fault detection technique based on time-varying autoregressive coefficients of IMFs as features is utilized. Sequential Karhunen-Loeve transform is employed on the condition indicators to select the appropriate window sizes on which SST can be applied. Laboratory experimental data obtained from drivetrain diagnostics simulator provides test bed to demonstrate the robustness of the proposed algorithm.en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSynchro-squeezing transform (SST)en
dc.subjectSequential Karhunen-Loeve transform (SKLT)en
dc.subjecttime-varying auto-regressive model (TVAR)en
dc.titleGearbox Fault Detection using Synchro-squeezing Transformen
dc.typeConference Paperen
dcterms.bibliographicCitationHazra, B., & Narasimhan, S. (2016). Gearbox Fault Detection Using Synchro-squeezing Transform. Procedia Engineering, 144, 187–194. https://doi.org/10.1016/j.proeng.2016.05.023en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Civil and Environmental Engineeringen
uws.typeOfResourceTexten
uws.typeOfResourceTexten
uws.scholarLevelFacultyen


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Attribution-NonCommercial-NoDerivatives 4.0 International
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