Diagnosis of bearing faults in induction motors by vibration signals-Comparison of multiple signal processing approaches

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dc.contributor.authorGoncalves, Mario J. M.
dc.contributor.authorCreppe, Renato C. [UNESP]
dc.contributor.authorMarques, Emanuel G.
dc.contributor.authorCruz, Sergio M. A.
dc.contributor.institutionInstituto de Telecomunicações
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T16:39:57Z
dc.date.available2018-12-11T16:39:57Z
dc.date.issued2015-01-01
dc.description.abstractEarly detection of faults in the bearings of electric motors is vital to reduce maintenance costs of industrial motors. Vibration signal analysis is a well-known and widely used diagnostic approach for bearing fault identification, and usually leads to good results in terms of effectiveness and detection capability. However, small defects, at an early stage of development, can be hard to find and require advanced signal processing techniques to facilitate the extraction of the fault characteristic frequencies from the noisy vibration signals. This work compares three different techniques applied to vibration signals to facilitate the extraction of the fault frequency components, namely the Teager-Kaiser operator, discrete wavelet transform and the Hilbert transform. A test bench was built and several types of defects were introduced in the motor bearings to compare vibration signals obtained with a healthy and a faulty motor. Comparative graphs of the results obtained with the three techniques are presented and the results are discussed.en
dc.description.affiliationDepartment of Electrical and Computer Engineering University of Coimbra Instituto de Telecomunicações
dc.description.affiliationDepartment of Electrical Engineering Univ. Estadual Paulista-UNESP School of Engineering
dc.description.affiliationUnespDepartment of Electrical Engineering Univ. Estadual Paulista-UNESP School of Engineering
dc.format.extent488-493
dc.identifierhttp://dx.doi.org/10.1109/ISIE.2015.7281516
dc.identifier.citationIEEE International Symposium on Industrial Electronics, v. 2015-September, p. 488-493.
dc.identifier.doi10.1109/ISIE.2015.7281516
dc.identifier.scopus2-s2.0-84947264367
dc.identifier.urihttp://hdl.handle.net/11449/168149
dc.language.isoeng
dc.relation.ispartofIEEE International Symposium on Industrial Electronics
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectBearing faults
dc.subjectdiagnostics
dc.subjectdiscrete wavelets
dc.subjectHilbert transform
dc.subjectinduction motor
dc.subjectTeager-Kaiser Operator
dc.titleDiagnosis of bearing faults in induction motors by vibration signals-Comparison of multiple signal processing approachesen
dc.typeTrabalho apresentado em evento

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