Recognition of simple and complex interacting non-orthogonal features

摘要

Feature recognition systems that deal with non-orthogonal features are seldom reported. This paper addresses this gap in the research by presenting a neural network-based feature recognition system to deal with non-orthogonal interacting features. The system accesses the B-rep data of a solid model, and searches for the feature volumes, using a cross-sectional layer method. The volumes are then transformed into 2D patterns of edges and vertices, using the conventions of ‘crosses and dots’ and ‘solid and dashed lines’. These feature patterns are later translated into input matrices for the recognition by a multilayer feedforward neural network.