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dc.contributor.author
Marti Puig, Pere
dc.contributor.author
Cusidó, Jordi
dc.contributor.author
Lozano, Francisco J.
dc.contributor.author
Serra Serra, Moises
dc.contributor.author
Caiafa, César Federico
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dc.contributor.author
Solé Casals, Jordi
dc.date.available
2023-11-01T17:58:34Z
dc.date.issued
2022-09
dc.identifier.citation
Marti Puig, Pere; Cusidó, Jordi; Lozano, Francisco J.; Serra Serra, Moises; Caiafa, César Federico; et al.; Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines; MDPI; Applied Sciences (Switzerland); 12; 19; 9-2022; 1-21
dc.identifier.issn
2076-3417
dc.identifier.uri
http://hdl.handle.net/11336/216800
dc.description.abstract
In this paper, the time variation of signals from several SCADA systems of geographically closed turbines are analysed and compared. When operating correctly, they show a clear pattern of joint variation. However, the presence of a failure in one of the turbines causes the signals from the faulty turbine to decouple from the pattern. From this information, SCADA data is used to determine, firstly, how to derive reference signals describing this pattern and, secondly, to compare the evolution of different turbines with respect to this joint variation. This makes it possible to determine whether the behaviour of the assembly is correct, because they maintain the well-functioning patterns, or whether they are decoupled. The presented strategy is very effective and can provide important support for decision making in turbine maintenance and, in the near future, to improve the classification of signals for training supervised normality models. In addition to being a very effective system, it is a low computational cost strategy, which can add great value to the SCADA data systems present in wind farms.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
MDPI
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/
dc.subject
FAULT DIAGNOSIS
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FEATURE ENGINEERING
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NORMAL BEHAVIOUR MODELS
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RENEWABLE ENERGY
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WIND TURBINE
dc.subject.classification
Ingeniería del Petróleo, Energía y Combustibles
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dc.subject.classification
Ingeniería del Medio Ambiente
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dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
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dc.title
Detection of Wind Turbine Failures through Cross-Information between Neighbouring Turbines
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-11-01T15:35:01Z
dc.journal.volume
12
dc.journal.number
19
dc.journal.pagination
1-21
dc.journal.pais
Suiza
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dc.description.fil
Fil: Marti Puig, Pere. Universidad Politécnica de Catalunya; España
dc.description.fil
Fil: Cusidó, Jordi. Universidad Politécnica de Catalunya; España
dc.description.fil
Fil: Lozano, Francisco J.. Universitat Oberta de Catalunya; España
dc.description.fil
Fil: Serra Serra, Moises. Universidad Politécnica de Catalunya; España
dc.description.fil
Fil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; Argentina
dc.description.fil
Fil: Solé Casals, Jordi. Universidad Politécnica de Catalunya; España
dc.journal.title
Applied Sciences (Switzerland)
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2076-3417/12/19/9491
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/app12199491
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