AUTOMATIC FORM-FEATURE RECOGNITION USING NEURAL-NETWORK-BASED TECHNIQUES ON BOUNDARY REPRESENTATIONS OF SOLID MODELS

A new technique for performing form-feature recognition using the principles of neural net works is discussed. Neural nets require parallel input of data, which, in this case, are B-rep solid models of parts. An input format has been developed which includes face descriptions and face-face relationships. An algorithm for recognition using neural-net-based techniques has been developed, and a suitable net architecture, which is similar to the multilayer perceptron in function and which implements the algorithm, has been designed. The net architecture is described, and a few examples are presented which highlight the strengths and weaknesses of the recognition algorithm.