Recognition and interpretation of interacting and non-interacting features using spatial decomposition and Hamiltonian path search

Since it is a complex task to formalize the feature recognition problem explicitly, a large variety of systems has been developed. One of the problems these systems have to overcome is the recognition and interpretation of interacting features. A fair success has been achieved in surface based methods to recognize certain classes of interacting features. However the problem remains for general cases of interacting features. Recently much effort has been focused on the volumetric approach. We present here the current state of a volumetric feature recognition method. The system considers interacting features in prismoidal parts and it operates in two stages: (1) recognition of regions of interest: a spatial decomposition of the space bounded by a predefined circumscribing volume is performed. A ‘cell evaluated and directed adjacency graph’ is then established. This graph is traversed to identify cavity volumes. (2) interpretation: cavity volumes made up of more than one cell can be produced by different machining operations. A graph-based decomposition method and Hamiltonian path search are combined to generate interpretations which correspond to optimal machining. The system CEDAG developed in this work uses a cell-face directed graph and contrasts the face-edge and edge-vertex graphs encountered in most conventional graph-based recognition methods.