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Development of a neural network to recognize standards and features from 3D CAD models

 
: Neb, Alexander; Briki, Iyed; Schönhof, Raoul

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Fulltext ()

Procedia CIRP 93 (2020), pp.1429-1434
ISSN: 2212-8271
Conference on Manufacturing Systems (CMS) <53, 2020, Online>
English
Journal Article, Conference Paper, Electronic Publication
Fraunhofer IPA ()
CAD Modeling; convolutional neural network; Erkennen; Fertigungsplanung

Abstract
Focus of this work is to recognize standards and further features directly from 3D CAD models. For this reason, a neural network was trained to recognize nine classes of machine elements. After the system identified a part as a standard, like a hexagon head screw after the DIN EN ISO 8676, it accesses the geometrical information of the CAD system via the Application Programming Interface (API). In the API, the system searches for necessary information to describe the part appropriately. Based on this information standardized parts can be recognized in detail and supplemented with further information.

: http://publica.fraunhofer.de/documents/N-622093.html