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ISSN      1003-9775
CN        11-2925/TP
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在线期刊

零件工序模型几何演变序列生成方法及应用

李春磊, 莫 蓉*, 常智勇, 杨海成, 张栋梁
(西北工业大学现代设计与集成制造技术教育部重点实验室 西安 710072)
分类号: TP391
出版年,卷(期):页码: 2017 , 29 ( 3 ): 565-574 李春磊
摘要: 针对机加工艺知识挖掘与重用困难的问题, 分析得出工艺知识隐藏在零件工序模型序列的几何变化之中, 并进一步提出工序模型几何演变序列的生成和相似性度量方法以及特征匹配算法. 首先对工序模型的几何变更进行提取和表示, 并将整个工序模型序列中所有前、后道工序间的几何变更按照工艺过程的优先级约束组成了几何演变序列; 然后建立零件工序模型几何演变序列的相似性度量算法, 并以算法的计算结果作为衡量零件工艺相似性的依据; 在几何演变序列中提取出参与特征形成过程的变更元素建立新的加工特征模型, 并通过构建特征的匹配算法来为融入加工特征形成过程的更高维的特征识别与匹配提供依据. 实例结果表明, 文中方法是可行性的.
关键词: 工序模型; 几何演变序列; 工艺知识; 工艺相似性度量; 加工特征识别
Generation Method and Applications of Geometry Variation Sequence of
Li Chunlei, Mo Rong*, Chang Zhiyong, Yang Haicheng, and Zhang Dongliang
(The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi’an 710072)
abstract: Machining process knowledge excavation and reuse is difficult because process knowledge is hidden in the geometry variation of intermediate process model sequence. A generation method of geometry variation sequence of intermediate process model, a process similarity measure algorithm, and a feature matching algo-rithm were presented in this paper. The geometry variation between the former procedure and the latter procedure is extracted and expressed, and the geometry variation sequence is set based on the precedence constraints of processing sequence. An algorithm of measuring similarity between geometry variation sequences is developed to evaluate the process similarity of parts. The geometry variation elements which is correlated with the formation of machining feature is extracted from the geometry variation sequence, and a new machining feature model is established. By applying feature model matching algorithm, features recognition and matching which integrates the formation process of features is realized. Experimental result shows that the effectiveness of proposed method is verified.
keyword: intermediate process model; geometry variation sequence; process knowledge; process similarity measure; ma-chining features recognition
 
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