Publicação
The role of automatic shape and position recognitionin streamlining manufacturing
| 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 |
|---|---|
| Autores principais: | Filipe, Ana I. |
| Outros Autores: | Costa, Carlos Alberto Pereira; Mendonca, Joao Pedro; Monteiro, A. Caetano |
| Assunto: | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| Ano: | 2015 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1866877959812415488 |
|---|---|
| author | Filipe, Ana I. |
| author2 | Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
| author2_role | author author author |
| author_facet | Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
| author_role | author |
| contributor_name_str_mv | Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Filipe, Ana I.\"},{\"Person.name\":\"Costa, Carlos Alberto Pereira\"},{\"Person.name\":\"Mendonca, Joao Pedro\"},{\"Person.name\":\"Monteiro, A. Caetano\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
| datacite.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2016-01-07T10:14:02Z |
| datacite.date.embargoed.fl_str_mv | 2016-01-07T10:14:02Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| datacite.titles.title.fl_str_mv | The role of automatic shape and position recognitionin streamlining manufacturing |
| dc.contributor.none.fl_str_mv | Universidade do Minho |
| dc.creator.none.fl_str_mv | Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
| dc.date.Accepted.fl_str_mv | 2015-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2016-01-07T10:14:02Z |
| dc.date.embargoed.fl_str_mv | 2016-01-07T10:14:02Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/39258 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | University of Montenegro. Center for Quality |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| dc.title.fl_str_mv | The role of automatic shape and position recognitionin streamlining manufacturing |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| 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 |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://prod-dspace.uminho.pt/bitstreams/78aebe4b-1042-4cd0-90a2-1353d38c71b7/download |
| id | rum_e8fb0edf52f34ee2fbc5fa4a46439167 |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/39258 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/39258 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Filipe, Ana I. Costa, Carlos Alberto Pereira Mendonca, Joao Pedro Monteiro, A. Caetano |
| publishDate | 2015 |
| publisher.none.fl_str_mv | University of Montenegro. Center for Quality |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engUniversity of Montenegro. Center for QualityporThe 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 proposedapplication/pdfporThe role of automatic shape and position recognitionin streamlining manufacturingFilipe, Ana I.Costa, Carlos Alberto PereiraMendonca, Joao PedroMonteiro, A. CaetanoHostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISSNIsPartOf1800-64502016-01-07T10:14:02Z20152015-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/39258http://purl.org/coar/access_right/c_abf2open accessGaussian curvaturesShape recognitionmetrologyConicityCylindricityFlatnessSphericity615329 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/78aebe4b-1042-4cd0-90a2-1353d38c71b7/download |
| spellingShingle | The role of automatic shape and position recognitionin streamlining manufacturing Filipe, Ana I. Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| status | SINGLETON |
| subject.fl_str_mv | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| title | 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_short | The role of automatic shape and position recognitionin streamlining manufacturing |
| title_sort | The role of automatic shape and position recognitionin streamlining manufacturing |
| topic | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| topic_facet | Gaussian curvatures Shape recognition metrology Conicity Cylindricity Flatness Sphericity |
| url | https://hdl.handle.net/1822/39258 |
| visible | 1 |