Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions

[EN] Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unf...

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Autores: Puche-Panadero, Rubén|||0000-0003-2090-1941, Martinez-Roman, Javier|||0000-0001-7544-8481, Sapena-Bano, Angel|||0000-0002-3888-6498, Burriel-Valencia, Jordi|||0000-0002-1680-4412, Riera-Guasp, Martín|||0000-0003-1327-242X
Tipo de recurso: artículo
Fecha de publicación:2020
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:10251/176420
Acceso en línea:https://riunet.upv.es/handle/10251/176420
Access Level:acceso abierto
Palabra clave:Analytic signal
Wavelet transform
Fault diagnosis
Induction machines
Spectrogram
Time-frequency domain
Wigner-Ville distribution
INGENIERIA ELECTRICA
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oai_identifier_str oai:riunet.upv.es:10251/176420
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
title Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
spellingShingle Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
Puche-Panadero, Rubén|||0000-0003-2090-1941
Analytic signal
Wavelet transform
Fault diagnosis
Induction machines
Spectrogram
Time-frequency domain
Wigner-Ville distribution
INGENIERIA ELECTRICA
title_short Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
title_full Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
title_fullStr Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
title_full_unstemmed Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
title_sort Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying Conditions
dc.creator.none.fl_str_mv Puche-Panadero, Rubén|||0000-0003-2090-1941
Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Burriel-Valencia, Jordi|||0000-0002-1680-4412
Riera-Guasp, Martín|||0000-0003-1327-242X
author Puche-Panadero, Rubén|||0000-0003-2090-1941
author_facet Puche-Panadero, Rubén|||0000-0003-2090-1941
Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Burriel-Valencia, Jordi|||0000-0002-1680-4412
Riera-Guasp, Martín|||0000-0003-1327-242X
author_role author
author2 Martinez-Roman, Javier|||0000-0001-7544-8481
Sapena-Bano, Angel|||0000-0002-3888-6498
Burriel-Valencia, Jordi|||0000-0002-1680-4412
Riera-Guasp, Martín|||0000-0003-1327-242X
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
AGENCIA ESTATAL DE INVESTIGACION
European Regional Development Fund
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Analytic signal
Wavelet transform
Fault diagnosis
Induction machines
Spectrogram
Time-frequency domain
Wigner-Ville distribution
INGENIERIA ELECTRICA
topic Analytic signal
Wavelet transform
Fault diagnosis
Induction machines
Spectrogram
Time-frequency domain
Wigner-Ville distribution
INGENIERIA ELECTRICA
description [EN] Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unfortunately, the MCSA method in its basic formulation can only be applied in steady state functioning. Nevertheless, every day increases the importance of inductions machines in applications such as wind generation, electric vehicles, or automated processes in which the machine works most of time under transient conditions. For these cases, new diagnostic methodologies have been proposed, based on the use of advanced time-frequency transforms-as, for example, the continuous wavelet transform, the Wigner Ville distribution, or the analytic function based on the Hilbert transform-which enables to track the fault components evolution along time. All these transforms have high computational costs and, furthermore, generate as results complex spectrograms, which require to be interpreted for qualified technical staff. This paper introduces a new methodology for the diagnosis of faults of IM working in transient conditions, which, unlike the methods developed up to today, analyzes the current signal in the slip-instantaneous frequency plane (s-IF), instead of the time-frequency (t-f) plane. It is shown that, in the s-IF plane, the fault components follow patterns that that are simple and unique for each type of fault, and thus does not depend on the way in which load and speed vary during the transient functioning; this characteristic makes the diagnostic task easier and more reliable. This work introduces a general scheme for the IMs diagnostic under transient conditions, through the analysis of the stator current in the s-IF plane. Another contribution of this paper is the introduction of the specific s-IF patterns associated with three different types of faults (rotor asymmetry fault, mixed eccentricity fault, and single-point bearing defects) that are theoretically justified and experimentally tested. As the calculation of the IF of the fault component is a key issue of the proposed diagnostic method, this paper also includes a comparative analysis of three different mathematical tools for calculating the IF, which are compared not only theoretically but also experimentally, comparing their performance when are applied to the tested diagnostic signals.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-06-01
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/10251/176420
url https://riunet.upv.es/handle/10251/176420
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTI2018-102175-B-I00-AR DISEÑO DE MODELOS AVANZADOS DE SIMULACION DE AEROGENERADORES PARA EL DESARROLLO Y PUESTA A PUNTO DE SISTEMAS DE DIAGNOSTICO DE AVERIAS "ON-LINE"
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
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
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI AG
publisher.none.fl_str_mv MDPI AG
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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spelling Fault Diagnosis in the Slip Frequency Plane of Induction Machines Working in Time-Varying ConditionsPuche-Panadero, Rubén|||0000-0003-2090-1941Martinez-Roman, Javier|||0000-0001-7544-8481Sapena-Bano, Angel|||0000-0002-3888-6498Burriel-Valencia, Jordi|||0000-0002-1680-4412Riera-Guasp, Martín|||0000-0003-1327-242XAnalytic signalWavelet transformFault diagnosisInduction machinesSpectrogramTime-frequency domainWigner-Ville distributionINGENIERIA ELECTRICA[EN] Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unfortunately, the MCSA method in its basic formulation can only be applied in steady state functioning. Nevertheless, every day increases the importance of inductions machines in applications such as wind generation, electric vehicles, or automated processes in which the machine works most of time under transient conditions. For these cases, new diagnostic methodologies have been proposed, based on the use of advanced time-frequency transforms-as, for example, the continuous wavelet transform, the Wigner Ville distribution, or the analytic function based on the Hilbert transform-which enables to track the fault components evolution along time. All these transforms have high computational costs and, furthermore, generate as results complex spectrograms, which require to be interpreted for qualified technical staff. This paper introduces a new methodology for the diagnosis of faults of IM working in transient conditions, which, unlike the methods developed up to today, analyzes the current signal in the slip-instantaneous frequency plane (s-IF), instead of the time-frequency (t-f) plane. It is shown that, in the s-IF plane, the fault components follow patterns that that are simple and unique for each type of fault, and thus does not depend on the way in which load and speed vary during the transient functioning; this characteristic makes the diagnostic task easier and more reliable. This work introduces a general scheme for the IMs diagnostic under transient conditions, through the analysis of the stator current in the s-IF plane. Another contribution of this paper is the introduction of the specific s-IF patterns associated with three different types of faults (rotor asymmetry fault, mixed eccentricity fault, and single-point bearing defects) that are theoretically justified and experimentally tested. As the calculation of the IF of the fault component is a key issue of the proposed diagnostic method, this paper also includes a comparative analysis of three different mathematical tools for calculating the IF, which are compared not only theoretically but also experimentally, comparing their performance when are applied to the tested diagnostic signals.This work was supported by the Spanish "Ministerio de Ciencia, Innovacion y Universidades (MCIU)", the "Agencia Estatal de Investigacion (AEI)" and the "Fondo Europeo de Desarrollo Regional (FEDER)" in the framework of the "Proyectos I+D+i -Retos Investigacion 2018", project reference RTI2018-102175-B-I00 (MCIU/AEI/FEDER, UE).MDPI AGEscuela Técnica Superior de Ingeniería Aeroespacial y Diseño IndustrialDepartamento de Ingeniería EléctricaInstituto Universitario de Investigación de Ingeniería EnergéticaEscuela Técnica Superior de Ingeniería IndustrialAGENCIA ESTATAL DE INVESTIGACIONEuropean Regional Development FundRepositorio Institucional de la Universitat Politècnica de València Riunet20202020-06-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/176420reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 RTI2018-102175-B-I00-AR DISEÑO DE MODELOS AVANZADOS DE SIMULACION DE AEROGENERADORES PARA EL DESARROLLO Y PUESTA A PUNTO DE SISTEMAS DE DIAGNOSTICO DE AVERIAS "ON-LINE"open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1764202026-06-13T07:49:27Z
score 15.228081

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