[1]乔虎,周源,白瑀.采用特征识别技术的MBD模型自动语义标注方法[J].华侨大学学报(自然科学版),2018,39(5):750-755.[doi:10.11830/ISSN.1000-5013.201804086]
　QIAO Hu,ZHOU Yuan,BAI Yu.Automatic Semantic Tagging of MBD Model Using Feature Recognition[J].Journal of Huaqiao University(Natural Science),2018,39(5):750-755.[doi:10.11830/ISSN.1000-5013.201804086]
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采用特征识别技术的MBD模型自动语义标注方法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第5期
页码:
750-755
栏目:
出版日期:
2018-09-20

文章信息/Info

Title:
Automatic Semantic Tagging of MBD Model Using Feature Recognition
文章编号:
1000-5013(2018)05-0750-06
作者:
乔虎;  周源;  白瑀
西安工业大学 机电工程学院, 陕西 西安 710021
Author(s):
QIAO Hu;  ZHOU Yuan;  BAI Yu
School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021, China
关键词:
语义标注;  特征识别;  MBD模型;  属性面邻接图
Keywords:
semantic tag;  feature recognition;  model based definition model;  attributed adjacency graphs
分类号:
TP391
DOI:
10.11830/ISSN.1000-5013.201804086
文献标志码:
A
摘要:
为了解决设计重用过程中基于模型的产品数字化定义(MBD)模型的问题,采用特征识别技术,对MBD模型自动添加语义标注,从而提高关键字检索的准确性.首先,对MBD模型的构成原理与模型要素进行分析,并在融合关键信息的基础上建立零件模型的属性面邻接图(AAG),根据零件模型上加工特征,将特征划分为螺钉头部特征、螺钉功能特征和材料特征.其次,通过顶点属性结合邻接矩阵重构图的顶点序列,动态编码结合距离匹配,求出最大公共子图,得出MBD模型之间的相似度.最后,利用聚类法实现对MBD模型的自动语义标注.实验结果表明:文中方法可以实现MBD模型的自动语义标注,很大程度上提高语义标注的自动化程度.
Abstract:
In order to solve the problem that it is difficult to obtain an model based definition(MBD)model, we use feature recognition technology to automatically add semantic annotation in MBD model to improve the accuracy of keyword search. Firstly, the composition principle and model elements of MBD model are analyzed and based on the fusion of key information, the attributed adjacency graphs(AAG)of the modelis established. According to the characteristics of the processing features on the part model, the features were divided into screw head features, screw functional characteristics and material characteristics. Combining vertex attribute with AAG’s adjacency. The maximum common graph representing the shape similarity of models is calculated by dynamic programming with the sequence of the graph nodes. Finally probability method is used to tag the MBD models automatically according to the similarity between the models. The experimental results show that the automatic semantic annotation of MBD model can be realized by using the method in this paper, and the degree of automation of semantic annotation is improved to a large extent.

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备注/Memo

备注/Memo:
收稿日期: 2018-04-16
通信作者: 乔虎(1986-),男,讲师,博士,主要从事数字化设计制造及三维模型检索的研究.E-mail:qiaonwpu@hotmail.com.
基金项目: 国家自然科学基金资助项目(51705392)
更新日期/Last Update: 2018-09-20