Delamination area quantification in composite structures using Gaussian process regression and auto-regressive models

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorLusófona University-
Autor(es): dc.contributorUniversidade do Porto-
Autor(es): dc.contributorChonnam National University-
Autor(es): dc.creatorPaixão, Jessé [UNESP]-
Autor(es): dc.creatorda Silva, Samuel [UNESP]-
Autor(es): dc.creatorFigueiredo, Eloi-
Autor(es): dc.creatorRadu, Lucian-
Autor(es): dc.creatorPark, Gyuhae-
Data de aceite: dc.date.accessioned2022-02-22T00:44:09Z-
Data de disponibilização: dc.date.available2022-02-22T00:44:09Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1177/1077546320966183-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/205373-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/205373-
Descrição: dc.descriptionAfter detecting initial delamination damage in a hotspot region of a composite structure monitored through a data-driven approach, the user needs to decide if there is an imminent structural failure or if the system can be kept in operation under monitoring to track the damage progression and its impact on the structural safety condition. Therefore, this study proposes delamination area quantification by stochastically interpolating global damage indices based on Gaussian process regression and taking into account uncertainty. Auto-regressive models are applied to extract damage-sensitive features from Lamb wave signals, and the Mahalanobis squared distance is used to compute damage indices. Two sets of laboratory tests are used to demonstrate the effectiveness of this methodology—one in carbon–epoxy laminate with simulated damage under temperature changes to show the general steps of the procedure, and a second test involving a set of carbon fiber–reinforced polymer coupons with actual delamination caused by repeated fatigue loads. Various levels of progression damage, measured by the covered area of delamination, are monitored using piezoelectric lead zirconate titanate patches bonded to the structural surfaces of these setups. The Gaussian process regression proved to be capable of accommodating the uncertainties to relate the damage indices versus the damaged area. The results exhibit a smooth and adequate prediction of the damaged area for both simulated damage and actual delamination.-
Descrição: dc.descriptionDepartamento de Engenharia Mecânica UNESP-Universidade Estadual Paulista-
Descrição: dc.descriptionFaculty of Engineering Lusófona University-
Descrição: dc.descriptionCONSTRUCT Faculdade de Engenharia Universidade do Porto-
Descrição: dc.descriptionDepartment of Mechanical Engineering Chonnam National University-
Descrição: dc.descriptionDepartamento de Engenharia Mecânica UNESP-Universidade Estadual Paulista-
Idioma: dc.languageen-
Relação: dc.relationJVC/Journal of Vibration and Control-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectauto-regressive models-
Palavras-chave: dc.subjectComposite structures-
Palavras-chave: dc.subjectdamage quantification-
Palavras-chave: dc.subjectdelamination-
Palavras-chave: dc.subjectGaussian process regression-
Palavras-chave: dc.subjectguided wave-
Título: dc.titleDelamination area quantification in composite structures using Gaussian process regression and auto-regressive models-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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