Identification of the level of contamination and degradation of oil by artificial neural networks

Detalhes bibliográficos
Autor(a) principal: da Silva, Ivan N. [UNESP]
Data de Publicação: 2000
Outros Autores: de Souza, Andre N. [UNESP], Hossri, Jose H. C., Zago, Maria G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ELINSL.2000.845506
http://hdl.handle.net/11449/224152
Resumo: This work presents the development of a new methodology through artificial neural networks to evaluate the level of contamination of the mineral oil used in transformers. This approach also concentrates on estimating the relative aging degree of transformers in relation to the main parameters that represent the degradation of the paper and insulating mineral oil. The results obtained in the simulations proved that the developed technique can be used as an alternative tool to become more suitable planning of the maintenance, allowing the decrease of costs involved in these operations.
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spelling Identification of the level of contamination and degradation of oil by artificial neural networksThis work presents the development of a new methodology through artificial neural networks to evaluate the level of contamination of the mineral oil used in transformers. This approach also concentrates on estimating the relative aging degree of transformers in relation to the main parameters that represent the degradation of the paper and insulating mineral oil. The results obtained in the simulations proved that the developed technique can be used as an alternative tool to become more suitable planning of the maintenance, allowing the decrease of costs involved in these operations.Univ of Sao Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, BauruMobile Transformer Oil Regeneration System-ECOIL Department of Electrical Engineering, CP 473, CEP 17033-360, BauruTransformers Zago Department of Electrical Engineering, CP 473, CEP 17033-360, BauruUniv of Sao Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, BauruUniversidade Estadual Paulista (UNESP)Mobile Transformer Oil Regeneration System-ECOILTransformers Zagoda Silva, Ivan N. [UNESP]de Souza, Andre N. [UNESP]Hossri, Jose H. C.Zago, Maria G.2022-04-28T19:54:57Z2022-04-28T19:54:57Z2000-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article275-279http://dx.doi.org/10.1109/ELINSL.2000.845506Conference Record of IEEE International Symposium on Electrical Insulation, p. 275-279.0164-2006http://hdl.handle.net/11449/22415210.1109/ELINSL.2000.8455062-s2.0-0033706660Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengConference Record of IEEE International Symposium on Electrical Insulationinfo:eu-repo/semantics/openAccess2022-04-28T19:54:57Zoai:repositorio.unesp.br:11449/224152Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:54:57Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Identification of the level of contamination and degradation of oil by artificial neural networks
title Identification of the level of contamination and degradation of oil by artificial neural networks
spellingShingle Identification of the level of contamination and degradation of oil by artificial neural networks
da Silva, Ivan N. [UNESP]
title_short Identification of the level of contamination and degradation of oil by artificial neural networks
title_full Identification of the level of contamination and degradation of oil by artificial neural networks
title_fullStr Identification of the level of contamination and degradation of oil by artificial neural networks
title_full_unstemmed Identification of the level of contamination and degradation of oil by artificial neural networks
title_sort Identification of the level of contamination and degradation of oil by artificial neural networks
author da Silva, Ivan N. [UNESP]
author_facet da Silva, Ivan N. [UNESP]
de Souza, Andre N. [UNESP]
Hossri, Jose H. C.
Zago, Maria G.
author_role author
author2 de Souza, Andre N. [UNESP]
Hossri, Jose H. C.
Zago, Maria G.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Mobile Transformer Oil Regeneration System-ECOIL
Transformers Zago
dc.contributor.author.fl_str_mv da Silva, Ivan N. [UNESP]
de Souza, Andre N. [UNESP]
Hossri, Jose H. C.
Zago, Maria G.
description This work presents the development of a new methodology through artificial neural networks to evaluate the level of contamination of the mineral oil used in transformers. This approach also concentrates on estimating the relative aging degree of transformers in relation to the main parameters that represent the degradation of the paper and insulating mineral oil. The results obtained in the simulations proved that the developed technique can be used as an alternative tool to become more suitable planning of the maintenance, allowing the decrease of costs involved in these operations.
publishDate 2000
dc.date.none.fl_str_mv 2000-01-01
2022-04-28T19:54:57Z
2022-04-28T19:54:57Z
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/ELINSL.2000.845506
Conference Record of IEEE International Symposium on Electrical Insulation, p. 275-279.
0164-2006
http://hdl.handle.net/11449/224152
10.1109/ELINSL.2000.845506
2-s2.0-0033706660
url http://dx.doi.org/10.1109/ELINSL.2000.845506
http://hdl.handle.net/11449/224152
identifier_str_mv Conference Record of IEEE International Symposium on Electrical Insulation, p. 275-279.
0164-2006
10.1109/ELINSL.2000.845506
2-s2.0-0033706660
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Conference Record of IEEE International Symposium on Electrical Insulation
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 275-279
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
_version_ 1799964693993881600

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