A symmetrical component feature extraction method for fault detection in induction machines

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dc.contributor.authorSt-Onge, Xavier F.
dc.contributor.authorCameron, James
dc.contributor.authorSaleh, Saleh
dc.contributor.authorScheme, Erik J.
dc.date.accessioned2023-12-21T18:58:36Z
dc.date.available2023-12-21T18:58:36Z
dc.date.issued2019-09
dc.description.abstractInduction motors (IMs) are among the fully developed electromechanical technologies that are still in use today. Over the course of the last century, their structure, control, and operation have been undergone through several stages of development. Among stages of development, the automated control and continuous monitoring of IMs has benefited from the emergence of modern artificial intelligence (AI) methods. IM automation schemes have demonstrated the ability to provide machine fault detection and diagnosis (FDD) function. AI-based FDD methods in IMs have employed frequency-domain, time-frequency, and time-domain analyses as the basis of their feature extraction schemes. A promising feature extraction scheme is one that uses symmetrical components (SCs) in time-domain FDD systems. Current SC-based approaches, however, are limited in their generalizability to different fault classes, may require detailed machine models, and can suffer from computational limitations. In this paper, an improved feature extraction method that uses SCs for a pattern recognition based FDD scheme for three-phase (3φ) IMs will be presented. This novel feature extraction method will be implemented and verified experimentally to demonstrate high classification performance, increased generalizability, and low computational cost.
dc.description.copyright© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37612
dc.language.isoen
dc.publisherIEEE
dc.relation.hasversionhttps://doi.org/10.1109/TIE.2018.2875644
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineElectrical and Computer Engineering
dc.titleA symmetrical component feature extraction method for fault detection in induction machines
dc.typejournal article
oaire.citation.endPage7289
oaire.citation.issue9
oaire.citation.startPage7281
oaire.citation.titleIEEE Transactions on Industrial Electronics
oaire.citation.volume66
oaire.license.conditionother
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa

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