Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/81688
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dc.creatorR. F. Mesquita Brandão
dc.creatorJ. A. Beleza Carvalho
dc.creatorFernando Maciel Barbosa
dc.date.accessioned2022-09-15T15:02:10Z-
dc.date.available2022-09-15T15:02:10Z-
dc.date.issued2015
dc.identifier.othersigarra:107874
dc.identifier.urihttps://hdl.handle.net/10216/81688-
dc.description.abstractNew generations of turbines have lower repair and maintenance costs than the previous generation. This is justified by the development of new components and materials. As the power of newer turbines is usually substantially larger, it is possible to get an economy of scale and lower maintenance costs per kW of rated power. This is simply because it is not needed to service a large turbine more often than a small one. New methods of earlier detection of faults are needed. The use of all information from SCADA (Supervisory Control and Data Acquisition) system can be useful, but it is necessary to develop tools to deal with bigger amount of information. Neural networks can help and turn possible new maintenance and operation schemes.
dc.language.isoeng
dc.relation.ispartofPowerTech2015
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectEngenharia electrotécnica, Engenharia electrotécnica, electrónica e informática
dc.subjectElectrical engineering, Electrical engineering, Electronic engineering, Information engineering
dc.titleIntelligent system for fault detection in wind turbines gearbox
dc.typeArtigo em Livro de Atas de Conferência Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.1109/PTC.2015.7232407
dc.identifier.authenticusP-00K-2S9
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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