车加工特征的自动识别与选择方法

提出一种车加工特征的自动识别和优化选择方法。首先，对于需要铣／车的零件，使用基于实体布尔运算的渐进式方法生成最大车加工体；然后，在毛坯和最大车加工体几何模型的基础上。生成需要切除材料的几何模型，并将该模型剖分为单元网格，形成属性化图的表示，根据属性化子图匹配算法统一地识别常规特征和用户自定义特征，形成零件车加工的原始特征集合；根据特征个数和方向数最小原则对原始特征集合进行优选和去冗余；最后，在相交特征之间选择特征前后顺序约束，使得按此顺序修剪后的特征重叠部分达到最少，以实现加工时间优化的目的。最后输出的是修剪后的非冗余特征集合及在其上的前后约束有向图。

Turning Feature Recognition and Selection

This paper presents an approach for recognizing and selecting features for parts to be turned. First, the maximum turnable model of the parts was found using a sequence of iterative Boolean operations. Then, the turning volume between the selected stock and the maximum turnable model was decomposed into a mesh and the mesh was further converted to an attributed graph. Based on the graph representation, graph-matching algorithm was applied to recognize ordinary and customized turning features, which form the primary feature set of the part. The primary feature set was condensed by removing redundant features and minimizing the numbers of features and their directions. Finally, in order to shorten the machining time, the remained features were trimmed according to the optimal feature precedences, which were selected using a criterion for minimizing overlapped volumes among the trimmed features.