MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION

Detalhes bibliográficos
Autor(a) principal: D'Angelo,Marcos F.S.V.
Data de Publicação: 2016
Outros Autores: Palhares,Reinaldo M., Maia,Renato D., Mendes,João B., Ekel,Petr Ya., Cangussu,Camila K.S., Aguiar,Lucas A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000200301
Resumo: ABSTRACT This paper addresses the problem of fault detection in stator winding of induction machine by a multiple change points detection approach in time series. To handle this problem a new fuzzy/Bayesian approach is proposed which differs from previous approaches since it does not require prior information as: the number of change points or the characterization of the data probabilistic distribution. The approach has been applied in the monitoring the current of the stator winding induction machine. The good results obtained by proposed methodology illustrate its efficiency.
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spelling MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTIONFuzzy/Bayesianmultiple change points detectionfault monitoringABSTRACT This paper addresses the problem of fault detection in stator winding of induction machine by a multiple change points detection approach in time series. To handle this problem a new fuzzy/Bayesian approach is proposed which differs from previous approaches since it does not require prior information as: the number of change points or the characterization of the data probabilistic distribution. The approach has been applied in the monitoring the current of the stator winding induction machine. The good results obtained by proposed methodology illustrate its efficiency.Sociedade Brasileira de Pesquisa Operacional2016-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000200301Pesquisa Operacional v.36 n.2 2016reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2016.036.02.0301info:eu-repo/semantics/openAccessD'Angelo,Marcos F.S.V.Palhares,Reinaldo M.Maia,Renato D.Mendes,João B.Ekel,Petr Ya.Cangussu,Camila K.S.Aguiar,Lucas A.eng2016-08-30T00:00:00Zoai:scielo:S0101-74382016000200301Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2016-08-30T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
title MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
spellingShingle MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
D'Angelo,Marcos F.S.V.
Fuzzy/Bayesian
multiple change points detection
fault monitoring
title_short MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
title_full MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
title_fullStr MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
title_full_unstemmed MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
title_sort MONITORING THE STATOR CURRENT IN INDUCTION MACHINES FOR POSSIBLE FAULT DETECTION: A FUZZY/BAYESIAN APPROACH FOR THE PROBLEM OF TIME SERIES MULTIPLE CHANGE POINT DETECTION
author D'Angelo,Marcos F.S.V.
author_facet D'Angelo,Marcos F.S.V.
Palhares,Reinaldo M.
Maia,Renato D.
Mendes,João B.
Ekel,Petr Ya.
Cangussu,Camila K.S.
Aguiar,Lucas A.
author_role author
author2 Palhares,Reinaldo M.
Maia,Renato D.
Mendes,João B.
Ekel,Petr Ya.
Cangussu,Camila K.S.
Aguiar,Lucas A.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv D'Angelo,Marcos F.S.V.
Palhares,Reinaldo M.
Maia,Renato D.
Mendes,João B.
Ekel,Petr Ya.
Cangussu,Camila K.S.
Aguiar,Lucas A.
dc.subject.por.fl_str_mv Fuzzy/Bayesian
multiple change points detection
fault monitoring
topic Fuzzy/Bayesian
multiple change points detection
fault monitoring
description ABSTRACT This paper addresses the problem of fault detection in stator winding of induction machine by a multiple change points detection approach in time series. To handle this problem a new fuzzy/Bayesian approach is proposed which differs from previous approaches since it does not require prior information as: the number of change points or the characterization of the data probabilistic distribution. The approach has been applied in the monitoring the current of the stator winding induction machine. The good results obtained by proposed methodology illustrate its efficiency.
publishDate 2016
dc.date.none.fl_str_mv 2016-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000200301
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382016000200301
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2016.036.02.0301
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.36 n.2 2016
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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