In machining feature recognition, geometric elements generated in a three-dimensional computer-aided design model are identified. This technique is used in manufacturability evaluation, process planning, and tool path generation. Here, we propose a method of recognizing 16 types of machining features using descriptors, often used in shape-based part retrieval studies. The base face is selected for each feature type, and descriptors express the base face's minimum, maximum, and equal conditions. Furthermore, the similarity in the three conditions between the descriptors extracted from the target face and those from the base face is calculated. If the similarity is greater than or equal to the threshold, the target face is determined as the base face of the feature. Machining feature recognition tests were conducted for two test cases using the proposed method, and all machining features included in the test cases were successfully recognized. Also, it was confirmed through an additional test that the proposed method in this study showed better feature recognition performance than the latest artificial neural network.
翻译:在机械化特征识别中,确定了在三维计算机辅助设计模型中产生的几何元素。该技术用于制造能力评估、流程规划和工具路径生成。在这里,我们建议一种方法,即使用描述器识别16种机械化特征,通常用于基于形状的部分检索研究。为每个特征类型选择了基面,描述器表达基面的最低、最大和同等条件。此外,还计算了从目标面提取的描述器与从基面提取的描述器在三种条件下的相似性。如果相似性大于或等于阈值,则目标面被确定为该特征的基础面貌。对两个测试案例使用拟议方法进行了断层特征识别测试,测试中包括的所有机械化特征都得到了成功识别。此外,通过补充测试确认,本研究中的拟议方法比最新的人工神经网络显示更好的特征识别性能。