Automatic recognition of features from freeform surface CAD models

This paper reports the design and implementation of a system for automatic recognition of features from freeform surface CAD models of sheet metal parts represented in STL format. The developed methodology has three major steps viz. STL model preprocessing, Region segmentation and automated Feature recognition. The input CAD model is preprocessed to get a healed and topology enriched STL model. A new hybrid region segmentation algorithm based on both edge- and region-based approaches has been developed to segment the preprocessed STL model into meaningful regions. Geometrical properties of facets, edges and vertices such as gauss and mean curvature at vertices, orientations of facet normals, shape structure of triangles, dihedral edge angle (angle between facets), etc. have been computed to identify and classify the regions. Feature on a freeform surface is defined as a set of connected meaningful regions having a particular geometry and topology which has some significance in design and manufacturing. Feature recognition rules have been formulated for recognizing a variety of protrusion and depression features such as holes, bends, darts, beads, louvres, dimples, dents, ridges/channels (blind and through) etc. occurring on automotive sheet metal panels. The developed system has been extensively tested with various industrial sheet metal parts and is found to be robust and consistent. The features data can be post processed and linked to various downstream CAD/CAM applications like automated process planning, sheet metal tool design, refinement of FEM meshes and product redesign. (C) 2008 Elsevier Ltd. All rights reserved.