Transfer Component Analysis for Compensation of Temperature Effects on the Impedance-Based Structural Health Monitoring

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorSilva, Samuel da [UNESP]-
Autor(es): dc.creatorYano, Marcus Omori [UNESP]-
Autor(es): dc.creatorGonsalez-Bueno, Camila Gianini [UNESP]-
Data de aceite: dc.date.accessioned2022-08-04T22:10:17Z-
Data de disponibilização: dc.date.available2022-08-04T22:10:17Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2021-09-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s10921-021-00794-6-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/221928-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/221928-
Descrição: dc.descriptionThe effects of temperature fluctuations in the impedance measurements’ spectral estimates confuse the procedures to distinguish actual states’ classification, demanding compensation. The present paper demonstrates a new method to achieve temperature compensation based on a Transfer Component Analysis (TCA), a subtype of transfer learning, of the features from a source domain (in a well-known labeled condition) to another target domain (in an unknown condition). This procedure assumes only the labeled features data in the healthy condition (baseline) and damaged state in a specific known temperature as source data. The features computed are the Root Mean Square Deviation (RMSD) indices of the real and imaginary impedance signals. A machine-learning algorithm based on Mahalanobis squared distance (D2) is trained using the features computed from the baseline condition in the reference temperature. Also, the other temperature and structural conditions data are assumed as testing data of the target condition. TCA’s main idea is mapping the features from the original features space to a new subspace where the detection becomes possible using the same training data in the source domain. The results performed in a testbench with a piezoelectric element (PZT) bonded under a set of temperatures monitored, and simulated damage confirmed that the proposed method could recognize the real states correctly by transferring the knowledge from the features of the source domain into the target domain, assuming different temperatures.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionDepartment of Mechanical Engineering São Paulo State University (UNESP), Avenida Brasil 56-
Descrição: dc.descriptionDepartment of Mechanical Engineering São Paulo State University (UNESP), Avenida Brasil 56-
Descrição: dc.descriptionCNPq: 306526/2019-0-
Descrição: dc.descriptionCAPES: 88882.433643/2019-01-
Idioma: dc.languageen-
Relação: dc.relationJournal of Nondestructive Evaluation-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectDomain adaptation-
Palavras-chave: dc.subjectElectromechanical impedance-
Palavras-chave: dc.subjectTemperature effects-
Palavras-chave: dc.subjectTransfer component analysis-
Título: dc.titleTransfer Component Analysis for Compensation of Temperature Effects on the Impedance-Based Structural Health Monitoring-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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