Separation techniques of partial discharges and electrical noise sources: A review of recent progress
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
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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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) |
repository.mail.fl_str_mv |
|
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1808128571902787584 |