Vast research works implementing feature-based technology have successfully been devoted. However, work on recognition of revolved regular-freeform surfaces is still inadequate due to its complex geometrical properties and topologies resulting lack of its physical significance. This paper presents a new method for recognising both regular and freeform revolved surfaces part model and generates its sub-delta volume using the volume decomposition method. To map the recognised sub-delta volume and respective machining process, part model complexity (PMC) is introduced. Generated sub-delta volumes are classified into three types of revolved surfaces excluding internal features. Sub-delta volumes are generated based on the machining process of roughing and finishing by offsetting the recognised faces. Internal features are de-featured by revolving respective sectioned faces. Differences of the overall delta volume ( $$\Delta {\text{ODV}}$$ Δ ODV ) were calculated and verifications of the proposed PMC were done and presented.

中文翻译：

---

通过增量体积生成对规则自由曲面的自动识别和零件模型复杂性量化

已经成功地投入了大量实施基于特征的技术的研究工作。然而，由于其复杂的几何特性和拓扑结构导致其缺乏物理意义，因此对旋转规则自由曲面的识别工作仍然不足。本文提出了一种识别规则和自由曲面零件模型的新方法，并使用体积分解方法生成其亚增量体积。为了映射识别的亚增量体积和相应的加工过程，引入了零件模型复杂性 (PMC)。生成的亚增量体积分为三种类型的旋转表面，不包括内部特征。通过偏移识别的面，基于粗加工和精加工的加工过程生成亚增量体积。通过旋转各自的截面来去除内部特征。计算了总增量体积 ($$\Delta {\text{ODV}}$$ Δ ODV ) 的差异，并对提议的 PMC 进行了验证和展示。