Identification of the level of contamination and degradation of oil by artificial neural networks
Autor(a) principal: | |
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Data de Publicação: | 2000 |
Outros Autores: | , , |
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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Repositório Institucional da UNESP |
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2946 |
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/openAccess2024-06-28T13:34:11Zoai:repositorio.unesp.br:11449/224152Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:55:07.927133Repositório 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_ |
1808128583070121984 |