Neural Networks for Condition Monitoring of Wind Turbines Gearbox

Detalhes bibliográficos
Autor(a) principal: Fernando Maciel Barbosa
Data de Publicação: 2012
Outros Autores: R. F. Mesquita Brandão, J. Beleza Carvalho
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/2654
Resumo: Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
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spelling Neural Networks for Condition Monitoring of Wind Turbines GearboxWind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.2017-11-16T13:57:10Z2012-01-01T00:00:00Z2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2654engFernando Maciel BarbosaR. F. Mesquita BrandãoJ. Beleza Carvalhoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:20Zoai:repositorio.inesctec.pt:123456789/2654Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:59.051588Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Neural Networks for Condition Monitoring of Wind Turbines Gearbox
title Neural Networks for Condition Monitoring of Wind Turbines Gearbox
spellingShingle Neural Networks for Condition Monitoring of Wind Turbines Gearbox
Fernando Maciel Barbosa
title_short Neural Networks for Condition Monitoring of Wind Turbines Gearbox
title_full Neural Networks for Condition Monitoring of Wind Turbines Gearbox
title_fullStr Neural Networks for Condition Monitoring of Wind Turbines Gearbox
title_full_unstemmed Neural Networks for Condition Monitoring of Wind Turbines Gearbox
title_sort Neural Networks for Condition Monitoring of Wind Turbines Gearbox
author Fernando Maciel Barbosa
author_facet Fernando Maciel Barbosa
R. F. Mesquita Brandão
J. Beleza Carvalho
author_role author
author2 R. F. Mesquita Brandão
J. Beleza Carvalho
author2_role author
author
dc.contributor.author.fl_str_mv Fernando Maciel Barbosa
R. F. Mesquita Brandão
J. Beleza Carvalho
description Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01T00:00:00Z
2012
2017-11-16T13:57:10Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/2654
url http://repositorio.inesctec.pt/handle/123456789/2654
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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