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

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorMobile Transformer Oil Regeneration System-ECOIL-
Autor(es): dc.contributorTransformers Zago-
Autor(es): dc.creatorda Silva, Ivan N.-
Autor(es): dc.creatorde Souza, Andre N.-
Autor(es): dc.creatorHossri, Jose H. C.-
Autor(es): dc.creatorZago, Maria G.-
Data de aceite: dc.date.accessioned2025-08-21T16:53:14Z-
Data de disponibilização: dc.date.available2025-08-21T16:53:14Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2000-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/ELINSL.2000.845506-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/224152-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/224152-
Descrição: dc.descriptionThis 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.-
Descrição: dc.descriptionUniv of Sao Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-
Descrição: dc.descriptionMobile Transformer Oil Regeneration System-ECOIL Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-
Descrição: dc.descriptionTransformers Zago Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-
Descrição: dc.descriptionUniv of Sao Paulo-UNESP Department of Electrical Engineering, CP 473, CEP 17033-360, Bauru-
Formato: dc.format275-279-
Idioma: dc.languageen-
Relação: dc.relationConference Record of IEEE International Symposium on Electrical Insulation-
???dc.source???: dc.sourceScopus-
Título: dc.titleIdentification of the level of contamination and degradation of oil by artificial neural networks-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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