Machine learning and image processing to monitor strain and tensile forces with mechanochromic sensors

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorde Castro, Lucas D.C.-
Autor(es): dc.creatorScabini, Leonardo-
Autor(es): dc.creatorRibas, Lucas C.-
Autor(es): dc.creatorBruno, Odemir M.-
Autor(es): dc.creatorOliveira, Osvaldo N.-
Data de aceite: dc.date.accessioned2025-08-21T21:19:42Z-
Data de disponibilização: dc.date.available2025-08-21T21:19:42Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-01-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.eswa.2022.118792-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/245896-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/245896-
Descrição: dc.descriptionA computer vision (CV) system is proposed for real-time prediction of strain by monitoring the color-changing feature of mechanochromic sensors. Pictures of the sensors subjected to calibration tensile tests were treated with standard image processing methods and analyzed using supervised machine learning (ML) algorithms. Visual strain sensing was demonstrated by linear regression models capable of learning a relation between the applied strain and the reflected structural color. The ElasticNet regression model provided the highest accuracy in the strain prediction task, with a remarkable performance in monitoring real-time strain variation of sensors during a tensile-relaxion cycle. Using calibration curves, the predicted strain can also be employed for estimating the tensile force applied on the mechanochromic sensors. Taken together these results point to potential intelligent systems for noninvasive in-situ visual monitoring of deformations and tensions.-
Descrição: dc.descriptionSão Carlos Institute of Physics University of São Paulo, SP-
Descrição: dc.descriptionInstitute of Biosciences Humanities and Exact Sciences São Paulo State University, SP-
Descrição: dc.descriptionInstitute of Biosciences Humanities and Exact Sciences São Paulo State University, SP-
Idioma: dc.languageen-
Relação: dc.relationExpert Systems with Applications-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectComputer vision-
Palavras-chave: dc.subjectImage processing-
Palavras-chave: dc.subjectMachine learning-
Palavras-chave: dc.subjectMechanochromic-
Palavras-chave: dc.subjectSensors-
Título: dc.titleMachine learning and image processing to monitor strain and tensile forces with mechanochromic sensors-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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