A New Projection Based Method for the Classification of Mechanical Components Using Convolutional Neural Networks. (May 2022)

• Record Type: Journal Article
• Authors: Bickel, S.; Schleich, B.; Wartzack, S.
• Is Part Of: Proceedings of the Design Society. Volume 2(2022)
• Page Start: 1501
• Page End: 1510
• Publication Date: 2022-05
• Subjects: data-driven design -- artificial intelligence (AI) -- data mining -- deep learning -- part classification; Industrial design -- Congresses; Engineering design -- Congresses; 620.0042
• DOI: 10.1017/pds.2022.152
• Languages: English
• ISSNs: 2633-7762

Abstract

Abstract: Digital engineering is increasingly established in the industrial routine. Especially the application of machine learning on geometry data is a growing research issue. Driven by this, the paper presents a new method for the classification of mechanical components, which utilizes the projection of points onto a spherical detector surfaces to transfer the geometries into matrices. These matrices are then classified using deep learning networks. Different types of projection are examined, as are several deep learning models. Finally, a benchmark dataset is used to demonstrate the competitiveness.