Recognition of machining features - a hybrid approach

Abstract

This paper describes a hybrid system which endeavours to recognize machining features automatically from a boundary representation (b-rep)-based solid modeller. The graph-based approach and the volume approach are adopted in consecutive stages in a prototype feature recognition system to combine the positive aspects of both strategies. The graph-based approach is based on feature edge sequence (FES) graph, a new graph structure introduced in this system. The FES graph approach is used to extract primitive features from the three-dimensional solid model; and the volume decomposition approach is incorporated to generate multiple interpretations of the feature sets. In addition, a neural network (NN)-based technique is used to tackle the problem of nonorthogonal and arbitrary features. Using the hybrid system, a workpiece designed in b-rep solid modeller will be interpreted and represented by a set of primitive features attached with significant manufacturing parameters, including multiple interpretations, tool directions and machining sequences, etc. The overall hybrid system is able to transform a pure geometric model into a machining feature-based model which is directly applicable for downstream manufacturing applications.