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Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes

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Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes

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dc.contributor.author Navarro-Jiménez, José-Manuel es_ES
dc.contributor.author Aguado, José V. es_ES
dc.contributor.author Bazin, Grégoire es_ES
dc.contributor.author ALBERO GABARDA, VICENTE es_ES
dc.contributor.author Borzacchiello, Domenico es_ES
dc.date.accessioned 2023-12-14T19:01:51Z
dc.date.available 2023-12-14T19:01:51Z
dc.date.issued 2023-06 es_ES
dc.identifier.issn 1572-8145 es_ES
dc.identifier.uri http://hdl.handle.net/10251/200769
dc.description.abstract [EN] Digitization of large parts with tight geometric tolerances is a time-consuming process that requires a detailed scan of the outer surface and the acquisition and processing of massive data. In this work, we propose a methodology for fast digitization using a partial scan in which large regions remain unmeasured. Our approach capitalizes on a database of fully scanned parts from which we extract a low-dimensional description of the shape variability using Statistical Shape Analysis. This lowdimensional description allows an accurate representation of any sample in the database with few independent parameters. Therefore, we propose a reconstruction algorithm that takes as input an incomplete measurement (faster than a complete digitization), identifies the statistical shape parameters and outputs a full scan reconstruction. We showcase an application to the digitization of large aeronautical fuselage panels. A statistical shape model is constructed from a database of 793 shapes that were completely digitized, with a point cloud of about 16 million points for each shape. Tests carried out at the manufacturing facility showed an overall reduction in the digitization time by 80% (using a partial digitization of 3 million points per shape) while keeping a high accuracy (reconstruction precision of 0.1mm) on the reconstructed surface. es_ES
dc.description.sponsorship The authors want to thank Stelia Aerospace for providing the data and their helpful support through the project, and also the financial support of the regional research consortium RFI Atlanstic2020 in Pays de la Loire, France. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Journal of Intelligent Manufacturing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Statistical shape analysis es_ES
dc.subject Shape reconstruction es_ES
dc.subject Surface digitization es_ES
dc.subject Sparse sampling es_ES
dc.subject.classification INGENIERIA MECANICA es_ES
dc.title Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10845-022-01918-z es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Ciencia y Tecnología del Hormigón - Institut de Ciència i Tecnologia del Formigó es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Navarro-Jiménez, J.; Aguado, JV.; Bazin, G.; Albero Gabarda, V.; Borzacchiello, D. (2023). Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes. Journal of Intelligent Manufacturing. 34(5):2345-2358. https://doi.org/10.1007/s10845-022-01918-z es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10845-022-01918-z es_ES
dc.description.upvformatpinicio 2345 es_ES
dc.description.upvformatpfin 2358 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 34 es_ES
dc.description.issue 5 es_ES
dc.relation.pasarela S\465898 es_ES
dc.contributor.funder Ministère de la Culture, Francia es_ES
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