Polynomial Chaos-Kriging metamodel for quantification of the debonding area in large wind turbine blades

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorIFMS—Instituto Federal de Mato Grosso do Sul-
Autor(es): dc.contributorUniversidade do Estado do Rio de Janeiro (UERJ)-
Autor(es): dc.contributorInstitute for Infrastructure and Environment-
Autor(es): dc.creatorPavlack, Bruna [UNESP]-
Autor(es): dc.creatorPaixão, Jessé [UNESP]-
Autor(es): dc.creatorda Silva, Samuel [UNESP]-
Autor(es): dc.creatorCunha, Americo-
Autor(es): dc.creatorGarcía Cava, David-
Data de aceite: dc.date.accessioned2022-02-22T00:46:48Z-
Data de disponibilização: dc.date.available2022-02-22T00:46:48Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1177/14759217211007956-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/206335-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/206335-
Descrição: dc.descriptionThis study aims to investigate the performance of a data-driven methodology for quantifying damage based on the use of a metamodel obtained from the Polynomial Chaos-Kriging method. The investigation seeks to quantify the severity of the damage, described by a specific type of debonding in a wind turbine blade as a function of a damage index. The damage indexes used are computed using a data-driven vibration-based structural health monitoring methodology. The blade’s debonding damage is introduced artificially, and the blade is excited with an electromechanical actuator that introduces a mechanical impulse causing the impact on the blade. The acceleration responses’ vibrations are measured by accelerometers distributed along the trailing and the wind turbine blade. A metamodel is formerly obtained through the Polynomial Chaos-Kriging method based on the damage indexes, trained with the blade’s healthy condition and four damage conditions, and validated with the other two damage conditions. The Polynomial Chaos-Kriging manifests promising results for capturing the proper trend for the severity of the damage as a function of the damage index. This research complements the damage detection analyses previously performed on the same blade.-
Descrição: dc.descriptionDepartamento de Engenharia Mecânica UNESP—Universidade Estadual Paulista-
Descrição: dc.descriptionIFMS—Instituto Federal de Mato Grosso do Sul-
Descrição: dc.descriptionUniversidade do Estado do Rio de Janeiro-
Descrição: dc.descriptionUniversity of Edinburgh School of Engineering Institute for Infrastructure and Environment-
Descrição: dc.descriptionDepartamento de Engenharia Mecânica UNESP—Universidade Estadual Paulista-
Idioma: dc.languageen-
Relação: dc.relationStructural Health Monitoring-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectdamage features-
Palavras-chave: dc.subjectdamage quantification-
Palavras-chave: dc.subjectdata-driven metamodel-
Palavras-chave: dc.subjectPolynomial Chaos-Kriging-
Palavras-chave: dc.subjectStructural health monitoring-
Palavras-chave: dc.subjectwind turbine blades-
Título: dc.titlePolynomial Chaos-Kriging metamodel for quantification of the debonding area in large wind turbine blades-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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