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面向三维机加工艺规划系统的CATIA模型B-Rep信息提取与应用
引用本文:徐同明,陈卓宁,李建勋. 面向三维机加工艺规划系统的CATIA模型B-Rep信息提取与应用[J]. 计算机系统应用, 2014, 23(6): 211-214
作者姓名:徐同明  陈卓宁  李建勋
作者单位:华中科技大学 机械科学与工程学院, 武汉 430074;华中科技大学 机械科学与工程学院, 武汉 430074;武汉开目信息技术有限责任公司, 武汉 430223;华中科技大学 机械科学与工程学院, 武汉 430074
摘    要:三维机加工艺规划设计是制造业信息化的重要组成部分,制造特征识别是其基础核心技术,是三维机加工艺规划设计的前提条件,其基础数据主要来源于产品三维模型底层的B-Rep(边界表示法)数据. 针对汽车等行业常用的CATIA三维模型B-Rep信息提取的关键技术及难点,介绍如何深入应用CAA二次开发技术,提取零件的B-Rep信息并应用于三维机加工艺规划艺系统的特征识别技术,为三维机加工艺规划过程提供了基础依据.

关 键 词:B-Rep  制造特征  特征识别  信息提取
收稿时间:2013-10-21
修稿时间:2013-11-19

Extraction and Application of CATIA Model B-Rep Information Oriented to Three-Dimensional Machining Process Planning System
XU Tong-Ming,CHEN Zhuo-Ning and LI Jian-Xun. Extraction and Application of CATIA Model B-Rep Information Oriented to Three-Dimensional Machining Process Planning System[J]. Computer Systems& Applications, 2014, 23(6): 211-214
Authors:XU Tong-Ming  CHEN Zhuo-Ning  LI Jian-Xun
Affiliation:School of Mechanical Science &Engineering, Huazhong University of Science &Technology, Wuhan 430074, China;School of Mechanical Science &Engineering, Huazhong University of Science &Technology, Wuhan 430074, China;Kaimu Information Technology Ltd, Wuhan 430223, China;School of Mechanical Science &Engineering, Huazhong University of Science &Technology, Wuhan 430074, China
Abstract:Three-Dimensional machining process planning is the important part of the manufacturing industry informationization, of which manufacturing feature recognition is the core technology which is the prerequisites of machining process planning. Its data mainly comes from the basal B-Rep(Boundary Representation) information of three-dimensional model. This paper focuses on the pivotal technic and difficulty of B-Rep information's extraction in CATIA which is commonly used in auto trade, describing how to apply CAA secondary development technology in depth, extract B-Rep information and use it to feature recognition technic of three-dimensional machining process planning system, providing a basis for machining process planning.
Keywords:B-Rep  manufacturing feature  feature recognition  information extraction
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