This paper presents an approach for recognizing both isolated and intersecting geometric features of freeform surface models of parts,for the purpose of automating the process planning of sheet metal forming.The devel...This paper presents an approach for recognizing both isolated and intersecting geometric features of freeform surface models of parts,for the purpose of automating the process planning of sheet metal forming.The developed methodology has three major steps:subdivision of B-spline surfaces,detection of protrusions and depressions,and recognition of geometric features for sheet metal forming domain.The input geometry data format of the part is based on an IGES CAD surface model represented in the form of trimmed B-spline surfaces.Each surface is classified or subdivided into different curvature regions with the aid of curvature property surfaces obtained by using symbolic computation of B-spline surfaces.Those regions satisfying a particular geometry and topology relation are recognized as protrusion and depression(DP) shapes.The DP shapes are then classified into different geometric features using a rule-based approach.A verified feasibility study of the developed method is also presented.展开更多
文摘This paper presents an approach for recognizing both isolated and intersecting geometric features of freeform surface models of parts,for the purpose of automating the process planning of sheet metal forming.The developed methodology has three major steps:subdivision of B-spline surfaces,detection of protrusions and depressions,and recognition of geometric features for sheet metal forming domain.The input geometry data format of the part is based on an IGES CAD surface model represented in the form of trimmed B-spline surfaces.Each surface is classified or subdivided into different curvature regions with the aid of curvature property surfaces obtained by using symbolic computation of B-spline surfaces.Those regions satisfying a particular geometry and topology relation are recognized as protrusion and depression(DP) shapes.The DP shapes are then classified into different geometric features using a rule-based approach.A verified feasibility study of the developed method is also presented.
