Separation techniques of partial discharges and electrical noise sources: A review of recent progress

Detalhes bibliográficos
Autor(a) principal: Ardila-Rey, Jorge Alfredo
Data de Publicação: 2020
Outros Autores: Cerda-Luna, Matías Patricio, Rozas-Valderrama, Rodrigo Andrés, De Castro, Bruno Albuquerque [UNESP], Andreoli, André Luiz [UNESP], Muhammad-Sukki, Firdaus
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ACCESS.2020.3035249
http://hdl.handle.net/11449/207479
Resumo: Partial discharge (PD) monitoring is one of the most used tools for diagnosing the condition of electrical equipment and machines that operate normally at high voltage levels. Ideally, PD identification can be easily done if there is a single source acting over the electrical asset during the measurement. However, in industrial environments, it is common to find the presence of multiple sources acting simultaneously, which hinders the identification process, due to sources of greater amplitude hiding the presence of other types of sources of lesser amplitude that could eventually be much more harmful to the insulation system. In this sense, the separation of PD through the use of clustering techniques allows individual source recognition once they have been clearly separated. This article describes the main clustering techniques that have been used over time to separate PD sources and electrical noise. The results obtained by the different authors in the utilization of each technique demonstrates good performance in terms of separation.
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spelling Separation techniques of partial discharges and electrical noise sources: A review of recent progressNoise sourcesPartial dischargesProgressReviewSeparation techniquesPartial discharge (PD) monitoring is one of the most used tools for diagnosing the condition of electrical equipment and machines that operate normally at high voltage levels. Ideally, PD identification can be easily done if there is a single source acting over the electrical asset during the measurement. However, in industrial environments, it is common to find the presence of multiple sources acting simultaneously, which hinders the identification process, due to sources of greater amplitude hiding the presence of other types of sources of lesser amplitude that could eventually be much more harmful to the insulation system. In this sense, the separation of PD through the use of clustering techniques allows individual source recognition once they have been clearly separated. This article describes the main clustering techniques that have been used over time to separate PD sources and electrical noise. The results obtained by the different authors in the utilization of each technique demonstrates good performance in terms of separation.Departamento de Ingeniería Eléctrica Universidad Técnica Federico Santa MaríaDepartment of Electrical Engineering Bauru School of Engineering São Paulo State University (UNESP)School of Engineering Robert Gordon UniversityDepartment of Electrical Engineering Bauru School of Engineering São Paulo State University (UNESP)Universidad Técnica Federico Santa MaríaUniversidade Estadual Paulista (Unesp)Robert Gordon UniversityArdila-Rey, Jorge AlfredoCerda-Luna, Matías PatricioRozas-Valderrama, Rodrigo AndrésDe Castro, Bruno Albuquerque [UNESP]Andreoli, André Luiz [UNESP]Muhammad-Sukki, Firdaus2021-06-25T10:55:54Z2021-06-25T10:55:54Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article199449-199461http://dx.doi.org/10.1109/ACCESS.2020.3035249IEEE Access, v. 8, p. 199449-199461.2169-3536http://hdl.handle.net/11449/20747910.1109/ACCESS.2020.30352492-s2.0-85102826184Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Accessinfo:eu-repo/semantics/openAccess2024-06-28T13:34:11Zoai:repositorio.unesp.br:11449/207479Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:50:27.842124Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Separation techniques of partial discharges and electrical noise sources: A review of recent progress
title Separation techniques of partial discharges and electrical noise sources: A review of recent progress
spellingShingle Separation techniques of partial discharges and electrical noise sources: A review of recent progress
Ardila-Rey, Jorge Alfredo
Noise sources
Partial discharges
Progress
Review
Separation techniques
title_short Separation techniques of partial discharges and electrical noise sources: A review of recent progress
title_full Separation techniques of partial discharges and electrical noise sources: A review of recent progress
title_fullStr Separation techniques of partial discharges and electrical noise sources: A review of recent progress
title_full_unstemmed Separation techniques of partial discharges and electrical noise sources: A review of recent progress
title_sort Separation techniques of partial discharges and electrical noise sources: A review of recent progress
author Ardila-Rey, Jorge Alfredo
author_facet Ardila-Rey, Jorge Alfredo
Cerda-Luna, Matías Patricio
Rozas-Valderrama, Rodrigo Andrés
De Castro, Bruno Albuquerque [UNESP]
Andreoli, André Luiz [UNESP]
Muhammad-Sukki, Firdaus
author_role author
author2 Cerda-Luna, Matías Patricio
Rozas-Valderrama, Rodrigo Andrés
De Castro, Bruno Albuquerque [UNESP]
Andreoli, André Luiz [UNESP]
Muhammad-Sukki, Firdaus
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidad Técnica Federico Santa María
Universidade Estadual Paulista (Unesp)
Robert Gordon University
dc.contributor.author.fl_str_mv Ardila-Rey, Jorge Alfredo
Cerda-Luna, Matías Patricio
Rozas-Valderrama, Rodrigo Andrés
De Castro, Bruno Albuquerque [UNESP]
Andreoli, André Luiz [UNESP]
Muhammad-Sukki, Firdaus
dc.subject.por.fl_str_mv Noise sources
Partial discharges
Progress
Review
Separation techniques
topic Noise sources
Partial discharges
Progress
Review
Separation techniques
description Partial discharge (PD) monitoring is one of the most used tools for diagnosing the condition of electrical equipment and machines that operate normally at high voltage levels. Ideally, PD identification can be easily done if there is a single source acting over the electrical asset during the measurement. However, in industrial environments, it is common to find the presence of multiple sources acting simultaneously, which hinders the identification process, due to sources of greater amplitude hiding the presence of other types of sources of lesser amplitude that could eventually be much more harmful to the insulation system. In this sense, the separation of PD through the use of clustering techniques allows individual source recognition once they have been clearly separated. This article describes the main clustering techniques that have been used over time to separate PD sources and electrical noise. The results obtained by the different authors in the utilization of each technique demonstrates good performance in terms of separation.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2021-06-25T10:55:54Z
2021-06-25T10:55:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ACCESS.2020.3035249
IEEE Access, v. 8, p. 199449-199461.
2169-3536
http://hdl.handle.net/11449/207479
10.1109/ACCESS.2020.3035249
2-s2.0-85102826184
url http://dx.doi.org/10.1109/ACCESS.2020.3035249
http://hdl.handle.net/11449/207479
identifier_str_mv IEEE Access, v. 8, p. 199449-199461.
2169-3536
10.1109/ACCESS.2020.3035249
2-s2.0-85102826184
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE Access
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 199449-199461
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)
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