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Título
Burr detection and classification using RUSTICO and image processing
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Journal of Computational Science
Datos de la obra
Riego, V., Sánchez-González, L., Fernández-Robles, L., Gutiérrez-Fernández, A., & Strisciuglio, N. (2021). Burr detection and classification using RUSTICO and image processing[Formula presented]. Journal of Computational Science, 56. https://doi.org/10.1016/J.JOCS.2021.101485
Editor
Elsevier
Fecha
2021
ISSN
1877-7503
Zusammenfassung
[EN] Machined workpieces must satisfy quality standards such as avoid the presence of burrs in edge finishing to reduce production costs and time. In this work we consider three types of burr that are determined by the distribution of the edge shape on a microscopic scale: knife-type (without imperfections), saw-type (presence of small splinters that could be accepted) and burr-breakage (substantial deformation that produces unusable workpieces). The proposed method includes RUSTICO to classify automatically the edge of each piece according to its burr type. Experimental results validate its effectiveness, yielding a 91.2% F1-Score and identifying completely the burr-breakage type.
Materia
Palabras clave
Peer review
SI
ID proyecto
- info: eu-repo/grantAgreement/AEI/Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i/PID2019-108277GB-C21/ES/DESARROLLO DE SISTEMAS DE FABRICACION COLABORATIVOS EN PLATAFORMAS DE INTERNET INDUSTRIALES
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