Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/5575 |
Resumo: | Nowadays, drilling of carbon/epoxy laminates is extremely frequent in manufacturing and assembling processes and is normally carried through using standard drills, like twist or Brad drills. However, it is always necessary to have in mind the need to adapt properly the drilling operations and/or the drilling tools used as the risk of delamination occurrence in the laminates involved, or other kind of damages, is very high. Moreover, delamination can be critical because the mechanical properties of the produced parts can be severely affected. Thus, the production of higher quality holes, with damage minimization, is a key challenge to everyone related with composites industry to develop adequate methodologies to delamination characterization and assessment. In this paper, the delamination caused on laminates by drilling machining operations is analytically evaluated by processing and analyzing enhanced conventional radiography images of the laminates involved. In resume, in order to evaluate the delamination damage in laminates plates caused by drilling operations, the radiography images acquired are processed using a computational methodology that uses techniques of image processing and analysis and a backpropagation artificial neural network. Experimental results show that the proposed methodology can be successfully used to measure and characterize the delaminated area. Hence, using our methodology, the damage evaluation on laminates can become more accurate, efficient and simple. |
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Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural networkTecnologiaTechnologyNowadays, drilling of carbon/epoxy laminates is extremely frequent in manufacturing and assembling processes and is normally carried through using standard drills, like twist or Brad drills. However, it is always necessary to have in mind the need to adapt properly the drilling operations and/or the drilling tools used as the risk of delamination occurrence in the laminates involved, or other kind of damages, is very high. Moreover, delamination can be critical because the mechanical properties of the produced parts can be severely affected. Thus, the production of higher quality holes, with damage minimization, is a key challenge to everyone related with composites industry to develop adequate methodologies to delamination characterization and assessment. In this paper, the delamination caused on laminates by drilling machining operations is analytically evaluated by processing and analyzing enhanced conventional radiography images of the laminates involved. In resume, in order to evaluate the delamination damage in laminates plates caused by drilling operations, the radiography images acquired are processed using a computational methodology that uses techniques of image processing and analysis and a backpropagation artificial neural network. Experimental results show that the proposed methodology can be successfully used to measure and characterize the delaminated area. Hence, using our methodology, the damage evaluation on laminates can become more accurate, efficient and simple.20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/5575engVictor Hugo C. de AlbuquerqueJoão Manuel R. S. TavaresLuís M. P. Durãoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:44:08Zoai:repositorio-aberto.up.pt:10216/5575Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:07:29.400184Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
title |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
spellingShingle |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network Victor Hugo C. de Albuquerque Tecnologia Technology |
title_short |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
title_full |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
title_fullStr |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
title_full_unstemmed |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
title_sort |
Evaluation of delamination damages on composite plates using techniques of image processing and analysis and a backpropagation artificial neural network |
author |
Victor Hugo C. de Albuquerque |
author_facet |
Victor Hugo C. de Albuquerque João Manuel R. S. Tavares Luís M. P. Durão |
author_role |
author |
author2 |
João Manuel R. S. Tavares Luís M. P. Durão |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Victor Hugo C. de Albuquerque João Manuel R. S. Tavares Luís M. P. Durão |
dc.subject.por.fl_str_mv |
Tecnologia Technology |
topic |
Tecnologia Technology |
description |
Nowadays, drilling of carbon/epoxy laminates is extremely frequent in manufacturing and assembling processes and is normally carried through using standard drills, like twist or Brad drills. However, it is always necessary to have in mind the need to adapt properly the drilling operations and/or the drilling tools used as the risk of delamination occurrence in the laminates involved, or other kind of damages, is very high. Moreover, delamination can be critical because the mechanical properties of the produced parts can be severely affected. Thus, the production of higher quality holes, with damage minimization, is a key challenge to everyone related with composites industry to develop adequate methodologies to delamination characterization and assessment. In this paper, the delamination caused on laminates by drilling machining operations is analytically evaluated by processing and analyzing enhanced conventional radiography images of the laminates involved. In resume, in order to evaluate the delamination damage in laminates plates caused by drilling operations, the radiography images acquired are processed using a computational methodology that uses techniques of image processing and analysis and a backpropagation artificial neural network. Experimental results show that the proposed methodology can be successfully used to measure and characterize the delaminated area. Hence, using our methodology, the damage evaluation on laminates can become more accurate, efficient and simple. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008 2008-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/5575 |
url |
https://hdl.handle.net/10216/5575 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799136000090308608 |