IR @ Goa University

Feature recognition from mesh models

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dc.contributor.author Tatkar, D.
dc.contributor.author Kelkar, G.
dc.contributor.author Kamat, V.V.
dc.date.accessioned 2017-07-26T09:53:18Z
dc.date.available 2017-07-26T09:53:18Z
dc.date.issued 2017
dc.identifier.citation International Journal of Computer Aided Engineering and Technology. 9(3); 2017; 289-306. en_US
dc.identifier.uri https://doi.org/10.1504/IJCAET.2017.084900
dc.identifier.uri http://irgu.unigoa.ac.in/drs/handle/unigoa/4872
dc.description.abstract In this paper, we propose a methodology for manufacturing feature recognition from a segmented triangulated mesh model. Proposed methodology has two phases, segment preprocessing and feature recognition. Input to the algorithm is triangulated mesh model which is simplified by segmenting the mesh model into high level regions approximated by a simple primitive such as planes, sphere and cylinders. In segment preprocessing phase, we gather adjacency information related to each identified primitive. For each feature to be identified, feature rules are defined using geometric properties of approximated primitives. Finally, feature recognition phase checks if any of the connected set of primitives satisfy the feature rules and highlights the recognised feature. At present, feature recognition is restricted only to simple features composed of plane primitives such as pocket, step, slot and cylindrical primitive such as holes. Given a segmented mesh model as an input, the algorithm automatically recognises different manufacturing features present in model. This extracted features information then can be used for downstream CAD/CAM application such as process planning, cost estimation and generating feature tree. en_US
dc.publisher InderScience en_US
dc.subject Computer Science and Technology en_US
dc.title Feature recognition from mesh models en_US
dc.type Journal article en_US
dc.identifier.impf cs


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