A Novel Approach Applied to Transient Short-Circuit Diagnosis in TIMs by Piezoelectric Sensors, PCA, and Wavelet Transform
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
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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Repositório Institucional da UNESP |
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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 |
|
_version_ |
1803649469213835264 |