Feature Recognition Of Hole, Slot And Free-formed Surface From Scanned Data Of Complex Model

Reverse engineering (RE) is the process of digitally capturing physical entities of an existing part from its scanned data. The current reverse engineering software can deal with some simple mechanical parts and surface, but may have problems of recognition precision, computing rate and shortage of functions. In some situation, the quality of reverse parts is related to the level of engineers'technique, especially for some complicated parts.This paper's aim is to develop an intelligent recognition system, which can extract complicated and similar features such as slot, boss and so on and improve the reverse recognition ability of the current software.A novel methodology is proposed for reconstruction of CAD models by recognizing prismatic features from a data set of three-dimensional scanned points, which utilizes the concepts of artificial neural networks (ANNs). Four geometric attributes, such as chain code, convex/concave, circular/rectangular, and open/closed attribute, are extracted from a scanned point set first, and then they are presented to the ANN module for feature recognition. Each generic feature in the feature library is uniquely described by those geometric attributes. Once these attributes are determined, a segmented point set may be uniquely identified as a valid feature through the ANN module.