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Diagnosis of Induction Motor Faults in the Fractional Fourier Domain

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Diagnosis of Induction Motor Faults in the Fractional Fourier Domain

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dc.contributor.author Pineda-Sanchez, Manuel es_ES
dc.contributor.author Riera-Guasp, Martín es_ES
dc.contributor.author Antonino-Daviu, J. es_ES
dc.contributor.author Roger-Folch, José es_ES
dc.contributor.author Perez-Cruz, Juan es_ES
dc.contributor.author Puche-Panadero, Rubén es_ES
dc.date.accessioned 2017-12-22T07:12:36Z
dc.date.available 2017-12-22T07:12:36Z
dc.date.issued 2010 es_ES
dc.identifier.issn 0018-9456 es_ES
dc.identifier.uri http://hdl.handle.net/10251/93322
dc.description.abstract [EN] Motor current signature analysis (MCSA) is a well-established method for the diagnosis of induction motor faults. It is based on the analysis of the spectral content of a motor current, which is sampled while a motor runs in steady state, to detect the harmonic components that characterize each type of fault. The Fourier transform (FT) plays a prominent role as a tool for identifying these spectral components. Recently, MCSA has also been applied during the transient regime (TMCSA) using the whole transient speed range to create a unique stamp of each harmonic as it evolves in the time-frequency plane. This method greatly enhances the reliability of the diagnostic process compared with the traditional method, which relies on spectral analysis at a single speed. However, the FT cannot be used in this case because the fault harmonics are not stationary signals. This paper proposes the use of the fractional FT (FrFT) instead of the FT to perform TMCSA. This paper also proposes the optimization of the FrFT to generate a spectrum where the frequency-varying fault harmonics appear as single spectral lines and, therefore, facilitate the diagnostic process. A discrete wavelet transform (DWT) is used as a conditioning tool to filter the motor current prior to its processing by the FrFT. Experimental results that are obtained with a 1.1-kW three-phase squirrel-cage induction motor with broken bars are presented to validate the proposed method. es_ES
dc.description.sponsorship This work was supported by the European Community's Seventh Framework Program FP7/2007-2013 under Grant Agreement 224233 (Research Project PRODI "Power Plant Robustification Based on Fault Detection and Isolation Algorithms"). The Associate Editor coordinating the review process for this paper was Dr. Subhas Mukhopadhyay.
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Transactions on Instrumentation and Measurement es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Failure analysis es_ES
dc.subject Fourier transforms (FTs) es_ES
dc.subject Induction motors es_ES
dc.subject Wavelet transforms (WTs) es_ES
dc.subject Time-frequency analysis es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Diagnosis of Induction Motor Faults in the Fractional Fourier Domain es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/TIM.2009.2031835 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/224233/EU/Power plants Robustification based On fault Detection and Isolation algorithms/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica es_ES
dc.description.bibliographicCitation Pineda-Sanchez, M.; Riera-Guasp, M.; Antonino-Daviu, J.; Roger-Folch, J.; Perez-Cruz, J.; Puche-Panadero, R. (2010). Diagnosis of Induction Motor Faults in the Fractional Fourier Domain. IEEE Transactions on Instrumentation and Measurement. 59(8):2065-2075. https://doi.org/10.1109/TIM.2009.2031835 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://doi.org/10.1109/TIM.2009.2031835 es_ES
dc.description.upvformatpinicio 2065 es_ES
dc.description.upvformatpfin 2075 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 59 es_ES
dc.description.issue 8 es_ES
dc.relation.pasarela S\37490 es_ES
dc.contributor.funder European Commission es_ES


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