Research On Machining Feature Recognition Of Box Parts Based On Graph And Rules

With the continuous development of computer technology,CAD?CAPP?CAM and other computer-aided software have been widely used in the machinery industry,which has greatly improved the efficiency of production process,but there are islands of information between these software,which makes it difficult to transform the design information in CAD software into the process information needed by the CAPP system completely.Feature recognition is treated as the key to solve this problem.This paper uses a graph and rule-based method to recognize machining features in box parts.It decomposes the attribute adjacency graph into several subgraphs to improve the efficiency of feature recognition.And the effectiveness of the algorithm is verified on the NX platform.The main research work of the thesis is as follows:(1)Analyze the structural characteristics of the box-like parts,and define the machining features of the box parts.Build an attribute adjacency graph for the three-dimensional model based on the B-rep structure,create several attributes,which extends the definition of the attribute adjacency graph.In order to eliminate the influence of blend features in feature recognition,this paper proposes a blend feature recognition and suppression algorithm to simplify the attribute adjacency graph.(2)Targeting at the problem that the traditional attribute adjacency graph secondary decomposition method cannot effectively deal with the problem of convex features,this paper proposes a decomposition method for attribute adjacency graph based on inner-loop edges and edge cycles,which connects the edges with same convexity as a cycle.Then the edges in cycles are disassembled to segregate the attribute adjacency graph into several subgraphs.Convex features are effectively separated by this method.After that,some subgraphs are rebuilt to restore the topological structure of intersection features.(3)This paper uses subgraph isomorphism as the method to match the machining features.The classic VF2 algorithm is expanded and optimized with the attributes in the attribute adjacency graph,which has led to a faster matching efficiency and few repeated matches.As for complex machining features,rule-based method is used to recognize features.Besides,this paper reorganizes the features by their positional relationships to recognize array features,which assures the accuracy and completeness of the algorithm.(4)Combined with the powerful secondary development API of NX,the feature recognition algorithm is implemented as a prototype system to recognize box machining features.Some typical box parts are selected to test the functionality of feature recognition algorithm in this paper.Experiments have shown that the system has a high recognizing accuracy on machining features in box parts.