Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime

[EN] Transient-based methods for fault diagnosis of induction machines (IMs) are attracting a rising interest, due to their reliability and ability to adapt to a wide range of IM's working conditions. These methods compute the time-frequency (TF) distribution of the stator current, where th...

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Autores: Burriel-Valencia, Jordi|||0000-0002-1680-4412, Puche-Panadero, Rubén|||0000-0003-2090-1941, Martinez-Roman, Javier|||0000-0001-7544-8481, Sapena-Bano, Angel|||0000-0002-3888-6498, Manuel Pineda-Sanchez|||0000-0001-7844-8831
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/103266
Acceso en línea:https://riunet.upv.es/handle/10251/103266
Access Level:acceso abierto
Palabra clave:Fault diagnosis
Induction machines
Short-frequency Fourier transform
Short-frequency time transform
Short-time Fourier transform
Spectrogram
Time-frequency distributions
INGENIERIA ELECTRICA
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repository_id_str
spelling Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient RegimeBurriel-Valencia, Jordi|||0000-0002-1680-4412Puche-Panadero, Rubén|||0000-0003-2090-1941Martinez-Roman, Javier|||0000-0001-7544-8481Sapena-Bano, Angel|||0000-0002-3888-6498Manuel Pineda-Sanchez|||0000-0001-7844-8831Fault diagnosisInduction machinesShort-frequency Fourier transformShort-frequency time transformShort-time Fourier transformSpectrogramTime-frequency distributionsINGENIERIA ELECTRICA[EN] Transient-based methods for fault diagnosis of induction machines (IMs) are attracting a rising interest, due to their reliability and ability to adapt to a wide range of IM's working conditions. These methods compute the time-frequency (TF) distribution of the stator current, where the patterns of the related fault components can be detected. A significant amount of recent proposals in this field have focused on improving the resolution of the TF distributions, allowing a better discrimination and identification of fault harmonic components. Nevertheless, as the resolution improves, computational requirements (power computing and memory) greatly increase, restricting its implementation in low-cost devices for performing on-line fault diagnosis. To address these drawbacks, in this paper, the use of the short-frequency Fourier transform (SFFT) for fault diagnosis of induction machines working under transient regimes is proposed. The SFFT not only keeps the resolution of traditional techniques, such as the short-time Fourier transform, but also achieves a drastic reduction of computing time and memory resources, making this proposal suitable for on-line fault diagnosis. This method is theoretically introduced and experimentally validated using a laboratory test bench.This work was supported by the Spanish Ministerio de Economia y Competitividad in the framework of the Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, under Project DPI2014-60881-R. The Associate Editor coordinating the review process was Dr. Edoardo Fiorucci.Institute of Electrical and Electronics EngineersEscuela Técnica Superior de Ingeniería Aeroespacial y Diseño IndustrialDepartamento de Ingeniería EléctricaInstituto Universitario de Investigación de Ingeniería EnergéticaEscuela Técnica Superior de Ingeniería IndustrialMinisterio de Economía, Industria y CompetitividadRepositorio Institucional de la Universitat Politècnica de València Riunet20172017-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/103266reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 DPI2014-60881-R VALUACION DE LA VIABILIDAD DE UN NUEVO PLANTEAMIENTO PARA EL SISTEMA DE DIAGNOSTICO DE AVERIAS EN LOS AEROGENERADORESopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1032662026-06-13T07:49:27Z
dc.title.none.fl_str_mv Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
title Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
spellingShingle Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
Burriel-Valencia, Jordi|||0000-0002-1680-4412
Fault diagnosis
Induction machines
Short-frequency Fourier transform
Short-frequency time transform
Short-time Fourier transform
Spectrogram
Time-frequency distributions
INGENIERIA ELECTRICA
title_short Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
title_full Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
title_fullStr Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
title_full_unstemmed Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
title_sort Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime
dc.creator.none.fl_str_mv Burriel-Valencia, Jordi|||0000-0002-1680-4412
Puche-Panadero, Rubén|||0000-0003-2090-1941
Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Manuel Pineda-Sanchez|||0000-0001-7844-8831
author Burriel-Valencia, Jordi|||0000-0002-1680-4412
author_facet Burriel-Valencia, Jordi|||0000-0002-1680-4412
Puche-Panadero, Rubén|||0000-0003-2090-1941
Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Manuel Pineda-Sanchez|||0000-0001-7844-8831
author_role author
author2 Puche-Panadero, Rubén|||0000-0003-2090-1941
Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Manuel Pineda-Sanchez|||0000-0001-7844-8831
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Escuela Técnica Superior de Ingeniería Aeroespacial y Diseño Industrial
Departamento de Ingeniería Eléctrica
Instituto Universitario de Investigación de Ingeniería Energética
Escuela Técnica Superior de Ingeniería Industrial
Ministerio de Economía, Industria y Competitividad
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Fault diagnosis
Induction machines
Short-frequency Fourier transform
Short-frequency time transform
Short-time Fourier transform
Spectrogram
Time-frequency distributions
INGENIERIA ELECTRICA
topic Fault diagnosis
Induction machines
Short-frequency Fourier transform
Short-frequency time transform
Short-time Fourier transform
Spectrogram
Time-frequency distributions
INGENIERIA ELECTRICA
description [EN] Transient-based methods for fault diagnosis of induction machines (IMs) are attracting a rising interest, due to their reliability and ability to adapt to a wide range of IM's working conditions. These methods compute the time-frequency (TF) distribution of the stator current, where the patterns of the related fault components can be detected. A significant amount of recent proposals in this field have focused on improving the resolution of the TF distributions, allowing a better discrimination and identification of fault harmonic components. Nevertheless, as the resolution improves, computational requirements (power computing and memory) greatly increase, restricting its implementation in low-cost devices for performing on-line fault diagnosis. To address these drawbacks, in this paper, the use of the short-frequency Fourier transform (SFFT) for fault diagnosis of induction machines working under transient regimes is proposed. The SFFT not only keeps the resolution of traditional techniques, such as the short-time Fourier transform, but also achieves a drastic reduction of computing time and memory resources, making this proposal suitable for on-line fault diagnosis. This method is theoretically introduced and experimentally validated using a laboratory test bench.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/103266
url https://riunet.upv.es/handle/10251/103266
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 DPI2014-60881-R VALUACION DE LA VIABILIDAD DE UN NUEVO PLANTEAMIENTO PARA EL SISTEMA DE DIAGNOSTICO DE AVERIAS EN LOS AEROGENERADORES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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