Você está no menu de acessibilidade

Utilize este identificador para citar ou criar um link para este item: http://acervodigital.unesp.br/handle/11449/68593
Registro de metadados completo
Campo DCValorIdioma
dc.contributor.authorDe Alcantara, N. P.-
dc.contributor.authorGasparini, M. E L-
dc.date.accessioned2014-05-27T11:21:43Z-
dc.date.accessioned2016-10-25T18:21:33Z-
dc.date.available2014-05-27T11:21:43Z-
dc.date.available2016-10-25T18:21:33Z-
dc.date.issued2005-12-01-
dc.identifierhttp://dx.doi.org/10.2529/PIERS041210092825-
dc.identifier.citationPIERS 2005 - Progress in Electromagnetics Research Symposium, Proceedings, p. 428-431.-
dc.identifier.urihttp://hdl.handle.net/11449/68593-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/68593-
dc.description.abstractThis work proposes a methodology for non destructive testing (NDT) of reinforced concrete structures, using superficial magnetic fields and artificial neural networks, in order to identify the size and position of steel bars, embedded into the concrete. For the purposes of this paper, magnetic induction curves were obtained by using a finite element program. Perceptron Multilayered (PML) ANNs, with Levemberg-Marquardt training algorithm were used. The results presented very good agreement with the expect ones, encouraging the development of real systems based upon the proposed methodology.en
dc.format.extent428-431-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectBackpropagation-
dc.subjectBars (metal)-
dc.subjectBuilding materials-
dc.subjectComposite beams and girders-
dc.subjectConcrete buildings-
dc.subjectConcrete construction-
dc.subjectConcrete testing-
dc.subjectElectric fault location-
dc.subjectKetones-
dc.subjectMagnetic field measurement-
dc.subjectMagnetic fields-
dc.subjectNondestructive examination-
dc.subjectPiers-
dc.subjectReinforced concrete-
dc.subjectSteel-
dc.subjectSteel testing-
dc.subjectArtificial neural networks-
dc.subjectFinite element programs-
dc.subjectMagnetic inductions-
dc.subjectMultilayered-
dc.subjectNon destructive testing-
dc.subjectPerceptron-
dc.subjectReal systems-
dc.subjectReinforced concrete structures-
dc.subjectSteel bars-
dc.subjectTraining algorithms-
dc.subjectNeural networks-
dc.titleSteel bars identification in reinforced concrete structures by using ANN and magnetic fieldsen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationSão Paulo State University-
dc.description.affiliationUnespSão Paulo State University-
dc.identifier.doi10.2529/PIERS041210092825-
dc.rights.accessRightsAcesso aberto-
dc.identifier.file2-s2.0-47949091143.pdf-
dc.relation.ispartofPIERS 2005 - Progress in Electromagnetics Research Symposium, Proceedings-
dc.identifier.scopus2-s2.0-47949091143-
Aparece nas coleções:Artigos, TCCs, Teses e Dissertações da Unesp

Não há nenhum arquivo associado com este item.
 

Itens do Acervo digital da UNESP são protegidos por direitos autorais reservados a menos que seja expresso o contrário.