Feature vector: a graph-based feature recognition methodology

Abstract

Recognition of machining features is a vital link for the effective integration of various modules of computer integrated manufacturing systems (CIMS). Graph-based recognition is the most researched method due to the sound mathematical background of graph theory and a graph's structural similarity with B-Rep computer-aided design modellers’ database. The method, however, is criticized for its high computational requirement of graph matching, its difficulty in building a feature template library, its ability to handle only polyhedral parts and its inability to handle interacting features. The paper reports a new edge classification scheme to extend the graph-based algorithms to handle test parts with curved faces. A unique method of representing a feature, called a feature vector, is developed. The feature vector generation heuristic results in a recognition system with polynomial time complexity for any arbitrary attributed adjacency graph. The feature vector can be generated automatically from B-Rep modellers. This helps in building incrementally a feature library as per the requirements of the specific domain. The proposed system is implemented in VC++ using an ACIS® 3D solid modelling toolkit.

Acknowledgement

The authors are thankful to Spatial Corporation, USA, for providing the ACIS 3D solid modelling toolkit under their university research development program.