Forecast of Faults in a Wind Turbine Gearbox

dc.contributor.author Fernando Maciel Barbosa en
dc.contributor.author R. F. Mesquita Brandão en
dc.contributor.author J. Beleza Carvalho en
dc.date.accessioned 2017-11-16T13:56:26Z
dc.date.available 2017-11-16T13:56:26Z
dc.date.issued 2012 en
dc.description.abstract The maintenance costs associated with wind turbines assumes an important weight in the operation of wind parks. The main objective of wind farms operators is to run their parks most economically, to increase their profits. An adequate maintenance planning is essential to an effective operating costs reduction, compared with traditional maintenance techniques. Tools to detect the onset of mechanical and electrical faults in wind turbines at a sufficiently early stage are very important for well planned maintenance actions, because these actions can reduce the outage time and can prevent bigger faults that can lead to machine outage. The amount of information obtained from SCADA systems of wind farms is huge. The use of neural networks to deal with all the information and try to detect faults in some equipment in a early stage is a promising technique en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/2644
dc.language eng en
dc.relation 4911 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Forecast of Faults in a Wind Turbine Gearbox en
dc.type conferenceObject en
dc.type Publication en
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