Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference

The rapid evolution of wind energy in reducing CO2 emissions worldwide is undeniable, which is, in fact, expected to continue or even increase its impressive yearly capacity growth. In this regard, optimizing operations and maintenance of wind turbines (WTs) and farms is considered to be one of the...

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Autores: Artigao Andicoberry, Estefanía, Ballester Arce, José Miguel, Bueso Sanchez, Maria del Carmen, Molina García, Ángel, Honrubia Escribano, Andrés, Gómez Lázaro, Emilio
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/41254
Acceso en línea:http://10.1109/ACCESS.2021.3090473
https://hdl.handle.net/10578/41254
Access Level:acceso abierto
Palabra clave:Circuit faults
Condition monitoring
Current signature analysis
Doubly fed induction generators
Doubly-fed induction generator
Mathematical model
Stators
Time series analysis
Vibrations
Wavelets
Wind turbines
Windowed scalogram difference
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spelling Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram DifferenceArtigao Andicoberry, EstefaníaBallester Arce, José MiguelBueso Sanchez, Maria del CarmenMolina García, ÁngelHonrubia Escribano, AndrésGómez Lázaro, EmilioCircuit faultsCondition monitoringCurrent signature analysisDoubly fed induction generatorsDoubly-fed induction generatorMathematical modelStatorsTime series analysisVibrationsWaveletsWind turbinesWindowed scalogram differenceThe rapid evolution of wind energy in reducing CO2 emissions worldwide is undeniable, which is, in fact, expected to continue or even increase its impressive yearly capacity growth. In this regard, optimizing operations and maintenance of wind turbines (WTs) and farms is considered to be one of the options for reducing the levelized cost of electricity of wind energy. This can be achieved by developing innovative condition monitoring methods. To this end, the use of the windowed scalogram difference (WSD) algorithm, based on wavelets, is proposed as an alternative solution, combined with current signature analysis (CSA). The electric generator is one of the major contributors to WT failure rates and downtime, and doubly-fed induction generators (DFIGs) are the dominant technology in variable-speed WTs. In the present work, operational data on an in-service WT DFIG are analyzed over a period of eight months, in contrast to the majority of the studies in this field, which rely on laboratory or simulated data. The evolution of the fault, namely rotor mechanical asymmetry, at an early stage, is analyzed and quantified implementing WSD to the stator current signals, supported by the previous diagnosis achieved through CSA. The combination of CSA and WSD shows strong potential for diagnosing and tracking, respectively, incipient faults in in-service WT DFIGs.IEEE202520252021info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://10.1109/ACCESS.2021.3090473https://hdl.handle.net/10578/41254reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésSBPLY/19/180501/000287info:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/412542026-05-27T07:36:41Z
dc.title.none.fl_str_mv Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
title Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
spellingShingle Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
Artigao Andicoberry, Estefanía
Circuit faults
Condition monitoring
Current signature analysis
Doubly fed induction generators
Doubly-fed induction generator
Mathematical model
Stators
Time series analysis
Vibrations
Wavelets
Wind turbines
Windowed scalogram difference
title_short Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
title_full Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
title_fullStr Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
title_full_unstemmed Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
title_sort Fault evolution monitoring of an in-service wind turbine DFIG using Windowed Scalogram Difference
dc.creator.none.fl_str_mv Artigao Andicoberry, Estefanía
Ballester Arce, José Miguel
Bueso Sanchez, Maria del Carmen
Molina García, Ángel
Honrubia Escribano, Andrés
Gómez Lázaro, Emilio
author Artigao Andicoberry, Estefanía
author_facet Artigao Andicoberry, Estefanía
Ballester Arce, José Miguel
Bueso Sanchez, Maria del Carmen
Molina García, Ángel
Honrubia Escribano, Andrés
Gómez Lázaro, Emilio
author_role author
author2 Ballester Arce, José Miguel
Bueso Sanchez, Maria del Carmen
Molina García, Ángel
Honrubia Escribano, Andrés
Gómez Lázaro, Emilio
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Circuit faults
Condition monitoring
Current signature analysis
Doubly fed induction generators
Doubly-fed induction generator
Mathematical model
Stators
Time series analysis
Vibrations
Wavelets
Wind turbines
Windowed scalogram difference
topic Circuit faults
Condition monitoring
Current signature analysis
Doubly fed induction generators
Doubly-fed induction generator
Mathematical model
Stators
Time series analysis
Vibrations
Wavelets
Wind turbines
Windowed scalogram difference
description The rapid evolution of wind energy in reducing CO2 emissions worldwide is undeniable, which is, in fact, expected to continue or even increase its impressive yearly capacity growth. In this regard, optimizing operations and maintenance of wind turbines (WTs) and farms is considered to be one of the options for reducing the levelized cost of electricity of wind energy. This can be achieved by developing innovative condition monitoring methods. To this end, the use of the windowed scalogram difference (WSD) algorithm, based on wavelets, is proposed as an alternative solution, combined with current signature analysis (CSA). The electric generator is one of the major contributors to WT failure rates and downtime, and doubly-fed induction generators (DFIGs) are the dominant technology in variable-speed WTs. In the present work, operational data on an in-service WT DFIG are analyzed over a period of eight months, in contrast to the majority of the studies in this field, which rely on laboratory or simulated data. The evolution of the fault, namely rotor mechanical asymmetry, at an early stage, is analyzed and quantified implementing WSD to the stator current signals, supported by the previous diagnosis achieved through CSA. The combination of CSA and WSD shows strong potential for diagnosing and tracking, respectively, incipient faults in in-service WT DFIGs.
publishDate 2021
dc.date.none.fl_str_mv 2021
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://10.1109/ACCESS.2021.3090473
https://hdl.handle.net/10578/41254
url http://10.1109/ACCESS.2021.3090473
https://hdl.handle.net/10578/41254
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv SBPLY/19/180501/000287
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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