The role of automatic shape and position recognitionin streamlining manufacturing
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/39258 |
Resumo: | The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed |
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The role of automatic shape and position recognitionin streamlining manufacturingGaussian curvaturesShape recognitionmetrologyConicityCylindricityFlatnessSphericityCiências Naturais::MatemáticasEngenharia e Tecnologia::Engenharia MecânicaScience & TechnologyThe main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposedCMAT, the Research Centre of Mathematics of the University of Minho with the Portuguese Funds from the “Fundação para a Ciência e a Tecnologia”, through the Project PEstOE/MAT/UI0013/2014; MEtRICs – (Mechanical Engineering and Resource Sustainability Center); CGIT - Centro de Gestão Industrial e da TecnologiaUniversity of Kragujevac. Faculty of Engineering. Center for QualityUniversidade do MinhoFilipe, Ana I.Costa, Carlos Alberto PereiraMendonca, Joao PedroMonteiro, A. Caetano20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/39258eng1800-6450http://www.ijqr.net/journal/v9-n1/4.pdfinfo: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:RCAAP2023-07-21T12:48:35Zoai:repositorium.sdum.uminho.pt:1822/39258Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:46:52.722096Repositório 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 |
The role of automatic shape and position recognitionin streamlining manufacturing |
title |
The role of automatic shape and position recognitionin streamlining manufacturing |
spellingShingle |
The role of automatic shape and position recognitionin streamlining manufacturing Filipe, Ana I. Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity Ciências Naturais::Matemáticas Engenharia e Tecnologia::Engenharia Mecânica Science & Technology |
title_short |
The role of automatic shape and position recognitionin streamlining manufacturing |
title_full |
The role of automatic shape and position recognitionin streamlining manufacturing |
title_fullStr |
The role of automatic shape and position recognitionin streamlining manufacturing |
title_full_unstemmed |
The role of automatic shape and position recognitionin streamlining manufacturing |
title_sort |
The role of automatic shape and position recognitionin streamlining manufacturing |
author |
Filipe, Ana I. |
author_facet |
Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
author_role |
author |
author2 |
Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
dc.subject.por.fl_str_mv |
Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity Ciências Naturais::Matemáticas Engenharia e Tecnologia::Engenharia Mecânica Science & Technology |
topic |
Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity Ciências Naturais::Matemáticas Engenharia e Tecnologia::Engenharia Mecânica Science & Technology |
description |
The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/39258 |
url |
https://hdl.handle.net/1822/39258 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1800-6450 http://www.ijqr.net/journal/v9-n1/4.pdf |
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.publisher.none.fl_str_mv |
University of Kragujevac. Faculty of Engineering. Center for Quality |
publisher.none.fl_str_mv |
University of Kragujevac. Faculty of Engineering. Center for Quality |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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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1799133039801925632 |