A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform

Detalhes bibliográficos
Autor(a) principal: Lucas, Guilherme Beraldi [UNESP]
Data de Publicação: 2023
Outros Autores: De Castro, Bruno Albuquerque [UNESP], Ardila-Rey, Jorge Alfredo, Glowacz, Adam, Leao, Jose Vital Ferraz [UNESP], Andreoli, Andre Luiz [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/JSEN.2023.3252816
http://hdl.handle.net/11449/248503
Resumo: Noninvasive fault diagnosis of three-phase induction motors (TIMs) is widely used in industrial applications to ensure the integrity of processes. Among different types of TIM failures, transient interturn short circuits (ITSCs) are incipient stator winding faults characterized as short circuits between two or more turns of the coils, that can lead the winding to progressive deterioration and, consequently, the TIM to total failure. In this context, this article proposes a novel approach by using piezoelectric transducers (PZTs), which performs the transient ITSC detection, phase identification, and magnitude classification by using the acoustic emission (AE) technique. To accomplish this analysis, a new statistical index based on the cross-correlation function was proposed to detect the ITSC and classify its magnitude. Besides, wavelet transform and principal component analysis (PCA) stood out as promising tools to identify which phase was affected by the short circuits. A TIM was subjected to ITSCs, and the experimental results showed that the proposed algorithm successfully performed the transient ITSC detection, phase identification, and evolution classification. In addition, this work improve the capabilities of traditional AE systems, since no AE signal processing algorithm has ever been proposed for a comprehensive diagnosis of transient ITSC.
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spelling A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet TransformAcoustic emission (AE)cross-correlation maximum value (CCMV)fault diagnosispiezoelectric sensorsprincipal component analysis (PCA)wavelet transformNoninvasive fault diagnosis of three-phase induction motors (TIMs) is widely used in industrial applications to ensure the integrity of processes. Among different types of TIM failures, transient interturn short circuits (ITSCs) are incipient stator winding faults characterized as short circuits between two or more turns of the coils, that can lead the winding to progressive deterioration and, consequently, the TIM to total failure. In this context, this article proposes a novel approach by using piezoelectric transducers (PZTs), which performs the transient ITSC detection, phase identification, and magnitude classification by using the acoustic emission (AE) technique. To accomplish this analysis, a new statistical index based on the cross-correlation function was proposed to detect the ITSC and classify its magnitude. Besides, wavelet transform and principal component analysis (PCA) stood out as promising tools to identify which phase was affected by the short circuits. A TIM was subjected to ITSCs, and the experimental results showed that the proposed algorithm successfully performed the transient ITSC detection, phase identification, and evolution classification. In addition, this work improve the capabilities of traditional AE systems, since no AE signal processing algorithm has ever been proposed for a comprehensive diagnosis of transient ITSC.São Paulo State University Department of Electrical Engineering, BauruUniversidad Técnica Federico Santa María Department of Electrical EngineeringAgh University of Science and Technology Department of Automatic Control and RoboticsSão Paulo State University Department of Electrical Engineering, BauruUniversidade Estadual Paulista (UNESP)Universidad Técnica Federico Santa MaríaAgh University of Science and TechnologyLucas, Guilherme Beraldi [UNESP]De Castro, Bruno Albuquerque [UNESP]Ardila-Rey, Jorge AlfredoGlowacz, AdamLeao, Jose Vital Ferraz [UNESP]Andreoli, Andre Luiz [UNESP]2023-07-29T13:45:45Z2023-07-29T13:45:45Z2023-04-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article8899-8908http://dx.doi.org/10.1109/JSEN.2023.3252816IEEE Sensors Journal, v. 23, n. 8, p. 8899-8908, 2023.1558-17481530-437Xhttp://hdl.handle.net/11449/24850310.1109/JSEN.2023.32528162-s2.0-85149851275Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Sensors Journalinfo:eu-repo/semantics/openAccess2024-06-28T13:34:10Zoai:repositorio.unesp.br:11449/248503Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-28T13:34:10Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
title A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
spellingShingle A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
Lucas, Guilherme Beraldi [UNESP]
Acoustic emission (AE)
cross-correlation maximum value (CCMV)
fault diagnosis
piezoelectric sensors
principal component analysis (PCA)
wavelet transform
title_short A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
title_full A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
title_fullStr A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
title_full_unstemmed A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
title_sort A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
author Lucas, Guilherme Beraldi [UNESP]
author_facet Lucas, Guilherme Beraldi [UNESP]
De Castro, Bruno Albuquerque [UNESP]
Ardila-Rey, Jorge Alfredo
Glowacz, Adam
Leao, Jose Vital Ferraz [UNESP]
Andreoli, Andre Luiz [UNESP]
author_role author
author2 De Castro, Bruno Albuquerque [UNESP]
Ardila-Rey, Jorge Alfredo
Glowacz, Adam
Leao, Jose Vital Ferraz [UNESP]
Andreoli, Andre Luiz [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidad Técnica Federico Santa María
Agh University of Science and Technology
dc.contributor.author.fl_str_mv Lucas, Guilherme Beraldi [UNESP]
De Castro, Bruno Albuquerque [UNESP]
Ardila-Rey, Jorge Alfredo
Glowacz, Adam
Leao, Jose Vital Ferraz [UNESP]
Andreoli, Andre Luiz [UNESP]
dc.subject.por.fl_str_mv Acoustic emission (AE)
cross-correlation maximum value (CCMV)
fault diagnosis
piezoelectric sensors
principal component analysis (PCA)
wavelet transform
topic Acoustic emission (AE)
cross-correlation maximum value (CCMV)
fault diagnosis
piezoelectric sensors
principal component analysis (PCA)
wavelet transform
description Noninvasive fault diagnosis of three-phase induction motors (TIMs) is widely used in industrial applications to ensure the integrity of processes. Among different types of TIM failures, transient interturn short circuits (ITSCs) are incipient stator winding faults characterized as short circuits between two or more turns of the coils, that can lead the winding to progressive deterioration and, consequently, the TIM to total failure. In this context, this article proposes a novel approach by using piezoelectric transducers (PZTs), which performs the transient ITSC detection, phase identification, and magnitude classification by using the acoustic emission (AE) technique. To accomplish this analysis, a new statistical index based on the cross-correlation function was proposed to detect the ITSC and classify its magnitude. Besides, wavelet transform and principal component analysis (PCA) stood out as promising tools to identify which phase was affected by the short circuits. A TIM was subjected to ITSCs, and the experimental results showed that the proposed algorithm successfully performed the transient ITSC detection, phase identification, and evolution classification. In addition, this work improve the capabilities of traditional AE systems, since no AE signal processing algorithm has ever been proposed for a comprehensive diagnosis of transient ITSC.
publishDate 2023
dc.date.none.fl_str_mv 2023-07-29T13:45:45Z
2023-07-29T13:45:45Z
2023-04-15
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/JSEN.2023.3252816
IEEE Sensors Journal, v. 23, n. 8, p. 8899-8908, 2023.
1558-1748
1530-437X
http://hdl.handle.net/11449/248503
10.1109/JSEN.2023.3252816
2-s2.0-85149851275
url http://dx.doi.org/10.1109/JSEN.2023.3252816
http://hdl.handle.net/11449/248503
identifier_str_mv IEEE Sensors Journal, v. 23, n. 8, p. 8899-8908, 2023.
1558-1748
1530-437X
10.1109/JSEN.2023.3252816
2-s2.0-85149851275
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE Sensors Journal
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 8899-8908
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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