粒子群优化三维模型相似性评价  

Improvement of 3D Mode Similarity Evaluation by Particle Swarm Optimization

作　　者：闫洁[1] 孙静懿[1] 韩文军 YAN Jie;SUN Jing-yi;HAN Wen-jun(ChangChun Finance College,Jilin Changchun130028,China;University of Electronic Science and Technology of China,Zhongshan College,Guangdong Zhongshan528400,China)

机构地区：[1]长春金融高等专科学校,吉林长春130028 [2]电子科技大学中山学院,广东中山528400

出　　处：《机械设计与制造》2020年第1期296-299,共4页Machinery Design & Manufacture

基　　金：吉林省教育科学“十三五”规划重点课题（ZD17177）

摘　　要：为了更好的度量三维CAD模型以实现面向设计领域的典型模型结构信息的智能重用,提出了基于粒子群算法优化的三维CAD模型典型结构挖掘和相似性评价方法。算法首先由组成模型各面的边的数目构造相似性评价矩阵,然后以此为描述体,通过粒子群算法搜索两模型的面最优匹配序列,最后根据搜索到的面最优序列提取并计算面相似度,进而对模型整体的相似度进行计算。通用ESB模型库实验结果表明,与已有算法相比,所提算法可以更准确地描述三维模型的典型结构相似性,有助于典型结构的准确挖掘和设计重用。In order to accurately measure the shape difference of the CAD model to better realize multi-granularity and intelligent reuse requirements,a similarity evaluation algorithm for 3 D CAD model based on particle swarm optimization is proposed. The similarity evaluation matrix from the number of edges that make up each face of the two models to be evaluated is constructed firstly,and then using that matrix as the descriptive body,the surface optimal matching sequence of the two models is searched through the particle swarm optimization algorithm. Finally,based on the searched optimal surface sequence,the surface similarity is extracted and calculated,and then the overall similarity evaluation of the two models is realized. Experimental results based on the general ESB model library show that,compared with the existing algorithms,the proposed algorithm can better evaluate the similarity of 3 D models,and facilitate accurate mining of typical structures to support local structural level design reuse of models.

关 键 词：典型结构重用 模型相似性评价 粒子群算法 最优匹配序列 

分 类 号：TH16[机械工程—机械制造及自动化] TP391.7[自动化与计算机技术—计算机应用技术]