Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/INDUSCON51756.2021.9529634 http://hdl.handle.net/11449/222500 |
Resumo: | Three-phase induction motors (TIMs) play a key role in the industrial scenario. Due to their robustness, low cost, and efficiency, TIMs have been increasingly used in industrial applications, making them the main source of electromechanical power to drive many types of loads. However, induction motors are eventually subjected to mechanical and electrical failures that can cause unexpected shutdowns. Among them, inter-turn short circuit faults (ITSC) in the stator windings correspond to the highest incidence of electrical faults in TIMs. These interruptions represent a high financial and operational cost. Therefore, the importance of detecting and identifying ITSC faults in the operation of TIMs increases. An analysis tool that shows a good result for a non-invasive technique (NIT) of damage diagnosis in induction motors is the study of mechanical vibration signals in the machine. In this paper, these signals were processed to identify and classify the ITSC faults present in the motor. For this purpose, a MEMS accelerometer was coupled to a TIM. Then, vibration signals were acquired for an ITSC fault present in each phase of the induction motor. The data was processed using the Hilbert transform energy and cross correlation. Thus, it was possible to detect the occurrence of an inter-turn short-circuit fault and identify in which phase the fault occurs by clustering the results. |
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Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transformDiagnosisElectrical machines and drivesIndustry applicationsPrognosis and system identificationThree-phase induction motors (TIMs) play a key role in the industrial scenario. Due to their robustness, low cost, and efficiency, TIMs have been increasingly used in industrial applications, making them the main source of electromechanical power to drive many types of loads. However, induction motors are eventually subjected to mechanical and electrical failures that can cause unexpected shutdowns. Among them, inter-turn short circuit faults (ITSC) in the stator windings correspond to the highest incidence of electrical faults in TIMs. These interruptions represent a high financial and operational cost. Therefore, the importance of detecting and identifying ITSC faults in the operation of TIMs increases. An analysis tool that shows a good result for a non-invasive technique (NIT) of damage diagnosis in induction motors is the study of mechanical vibration signals in the machine. In this paper, these signals were processed to identify and classify the ITSC faults present in the motor. For this purpose, a MEMS accelerometer was coupled to a TIM. Then, vibration signals were acquired for an ITSC fault present in each phase of the induction motor. The data was processed using the Hilbert transform energy and cross correlation. Thus, it was possible to detect the occurrence of an inter-turn short-circuit fault and identify in which phase the fault occurs by clustering the results.São Paulo State University (UNESP)São Paulo State University (UNESP)Universidade Estadual Paulista (UNESP)Rocha, Marco [UNESP]Lucas, Guilherme [UNESP]Souza, Wallace [UNESP]de Castro, Bruno Albuquerque [UNESP]Andreoli, André [UNESP]2022-04-28T19:45:08Z2022-04-28T19:45:08Z2021-08-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject955-961http://dx.doi.org/10.1109/INDUSCON51756.2021.95296342021 14th IEEE International Conference on Industry Applications, INDUSCON 2021 - Proceedings, p. 955-961.http://hdl.handle.net/11449/22250010.1109/INDUSCON51756.2021.95296342-s2.0-85115852885Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2021 14th IEEE International Conference on Industry Applications, INDUSCON 2021 - Proceedingsinfo:eu-repo/semantics/openAccess2022-04-28T19:45:08Zoai:repositorio.unesp.br:11449/222500Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:44:20.832850Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
title |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
spellingShingle |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform Rocha, Marco [UNESP] Diagnosis Electrical machines and drives Industry applications Prognosis and system identification |
title_short |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
title_full |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
title_fullStr |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
title_full_unstemmed |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
title_sort |
Detection and phase identification of inter-turn short-circuit faults in three-phase induction motors using MEMS accelerometer and Hilbert transform |
author |
Rocha, Marco [UNESP] |
author_facet |
Rocha, Marco [UNESP] Lucas, Guilherme [UNESP] Souza, Wallace [UNESP] de Castro, Bruno Albuquerque [UNESP] Andreoli, André [UNESP] |
author_role |
author |
author2 |
Lucas, Guilherme [UNESP] Souza, Wallace [UNESP] de Castro, Bruno Albuquerque [UNESP] Andreoli, André [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Rocha, Marco [UNESP] Lucas, Guilherme [UNESP] Souza, Wallace [UNESP] de Castro, Bruno Albuquerque [UNESP] Andreoli, André [UNESP] |
dc.subject.por.fl_str_mv |
Diagnosis Electrical machines and drives Industry applications Prognosis and system identification |
topic |
Diagnosis Electrical machines and drives Industry applications Prognosis and system identification |
description |
Three-phase induction motors (TIMs) play a key role in the industrial scenario. Due to their robustness, low cost, and efficiency, TIMs have been increasingly used in industrial applications, making them the main source of electromechanical power to drive many types of loads. However, induction motors are eventually subjected to mechanical and electrical failures that can cause unexpected shutdowns. Among them, inter-turn short circuit faults (ITSC) in the stator windings correspond to the highest incidence of electrical faults in TIMs. These interruptions represent a high financial and operational cost. Therefore, the importance of detecting and identifying ITSC faults in the operation of TIMs increases. An analysis tool that shows a good result for a non-invasive technique (NIT) of damage diagnosis in induction motors is the study of mechanical vibration signals in the machine. In this paper, these signals were processed to identify and classify the ITSC faults present in the motor. For this purpose, a MEMS accelerometer was coupled to a TIM. Then, vibration signals were acquired for an ITSC fault present in each phase of the induction motor. The data was processed using the Hilbert transform energy and cross correlation. Thus, it was possible to detect the occurrence of an inter-turn short-circuit fault and identify in which phase the fault occurs by clustering the results. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-15 2022-04-28T19:45:08Z 2022-04-28T19:45:08Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/INDUSCON51756.2021.9529634 2021 14th IEEE International Conference on Industry Applications, INDUSCON 2021 - Proceedings, p. 955-961. http://hdl.handle.net/11449/222500 10.1109/INDUSCON51756.2021.9529634 2-s2.0-85115852885 |
url |
http://dx.doi.org/10.1109/INDUSCON51756.2021.9529634 http://hdl.handle.net/11449/222500 |
identifier_str_mv |
2021 14th IEEE International Conference on Industry Applications, INDUSCON 2021 - Proceedings, p. 955-961. 10.1109/INDUSCON51756.2021.9529634 2-s2.0-85115852885 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2021 14th IEEE International Conference on Industry Applications, INDUSCON 2021 - Proceedings |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
955-961 |
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_ |
1808128411605925888 |