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
Feature recognition is a process of extracting machining features which has engineering meaning from solid model, and it is a key technology of CAD/CAPP/CAM integration. This paper presents an effective and efficient ...Feature recognition is a process of extracting machining features which has engineering meaning from solid model, and it is a key technology of CAD/CAPP/CAM integration. This paper presents an effective and efficient methodology of recognizing machining feature. In this approach, features are classified into two categories： pocket feature and predefined feature. Different feature type adopts its special hint and heuristic rule, and is helpful to recognize intersection feature. Feature classification optimizes search algorithm and shortens search scope dramatically. Meanwhile, extension and split algorithm is used to handle intersecting feature. Moreover, feature mapping based on machining knowledge is introduced to support downstream application better. Finally, case studies with complex intersecting features prove that the developed approach has stronger recognizing ability.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.
文摘Feature recognition is a process of extracting machining features which has engineering meaning from solid model, and it is a key technology of CAD/CAPP/CAM integration. This paper presents an effective and efficient methodology of recognizing machining feature. In this approach, features are classified into two categories： pocket feature and predefined feature. Different feature type adopts its special hint and heuristic rule, and is helpful to recognize intersection feature. Feature classification optimizes search algorithm and shortens search scope dramatically. Meanwhile, extension and split algorithm is used to handle intersecting feature. Moreover, feature mapping based on machining knowledge is introduced to support downstream application better. Finally, case studies with complex intersecting features prove that the developed approach has stronger recognizing ability.
