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

Autor:	Neb, Alexander, Briki, Iyed, Schoenhof, Raoul
Rok vydání:	2022
Předmět:	Computer Science - Graphics Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Zdroj:	Procedia CIRP Volume 93, 2020, Pages 1429-1434
Druh dokumentu:	Working Paper
DOI:	10.1016/j.procir.2020.03.010
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2202.00573 Zobrazit plný text záznamu View this record from Arxiv