Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes

Detalhes bibliográficos
Autor(a) principal: De Alcantara Jr., Naasson P. [UNESP]
Data de Publicação: 2002
Outros Autores: De Carvalho, Alexandre M. [UNESP], Ulson, Jose Alfredo Covolan [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/IJCNN.2002.1007730
http://hdl.handle.net/11449/66770
Resumo: This work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.
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spelling Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubesAgentsComputer simulationFinite element methodLeakage (fluid)Nondestructive examinationTubes (components)Atmospheric tubesMetallic tubesMultilayer neural networksThis work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.Electrical Engineering Department São Paulo State Univ.-UNESP, 17033-360 - Bauru - SPElectrical Engineering Department São Paulo State Univ.-UNESP, 17033-360 - Bauru - SPUniversidade Estadual Paulista (Unesp)De Alcantara Jr., Naasson P. [UNESP]De Carvalho, Alexandre M. [UNESP]Ulson, Jose Alfredo Covolan [UNESP]2014-05-27T11:20:23Z2014-05-27T11:20:23Z2002-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1450-1454http://dx.doi.org/10.1109/IJCNN.2002.1007730Proceedings of the International Joint Conference on Neural Networks, v. 2, p. 1450-1454.http://hdl.handle.net/11449/6677010.1109/IJCNN.2002.1007730WOS:0001774028002592-s2.0-00360887524517057121462258Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the International Joint Conference on Neural Networksinfo:eu-repo/semantics/openAccess2021-10-23T21:37:50Zoai:repositorio.unesp.br:11449/66770Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:37:50Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
title Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
spellingShingle Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
De Alcantara Jr., Naasson P. [UNESP]
Agents
Computer simulation
Finite element method
Leakage (fluid)
Nondestructive examination
Tubes (components)
Atmospheric tubes
Metallic tubes
Multilayer neural networks
title_short Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
title_full Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
title_fullStr Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
title_full_unstemmed Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
title_sort Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes
author De Alcantara Jr., Naasson P. [UNESP]
author_facet De Alcantara Jr., Naasson P. [UNESP]
De Carvalho, Alexandre M. [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
author_role author
author2 De Carvalho, Alexandre M. [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv De Alcantara Jr., Naasson P. [UNESP]
De Carvalho, Alexandre M. [UNESP]
Ulson, Jose Alfredo Covolan [UNESP]
dc.subject.por.fl_str_mv Agents
Computer simulation
Finite element method
Leakage (fluid)
Nondestructive examination
Tubes (components)
Atmospheric tubes
Metallic tubes
Multilayer neural networks
topic Agents
Computer simulation
Finite element method
Leakage (fluid)
Nondestructive examination
Tubes (components)
Atmospheric tubes
Metallic tubes
Multilayer neural networks
description This work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.
publishDate 2002
dc.date.none.fl_str_mv 2002-01-01
2014-05-27T11:20:23Z
2014-05-27T11:20:23Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/IJCNN.2002.1007730
Proceedings of the International Joint Conference on Neural Networks, v. 2, p. 1450-1454.
http://hdl.handle.net/11449/66770
10.1109/IJCNN.2002.1007730
WOS:000177402800259
2-s2.0-0036088752
4517057121462258
url http://dx.doi.org/10.1109/IJCNN.2002.1007730
http://hdl.handle.net/11449/66770
identifier_str_mv Proceedings of the International Joint Conference on Neural Networks, v. 2, p. 1450-1454.
10.1109/IJCNN.2002.1007730
WOS:000177402800259
2-s2.0-0036088752
4517057121462258
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the International Joint Conference on Neural Networks
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1450-1454
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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