A method for discrete quantization and similarity analysis of assembly model

被引：0
|
作者：
Zhang J. [1 ]
Ji B. [1 ]
Yang N. [1 ]
Tang W. [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an
[2] School of Mechanical and Electrical Engineering, Xi'an Polytechnic University, Xi'an
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2021年 / 42卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Assembly retrieval; BOW indexing; Similarity analysis; Structural discretization; Structure-shape distance;
D O I：
10.7527/S1000-6893.2021.24992
中图分类号：
学科分类号：
摘要：
Similarity analysis of the assembly model is widely concerned in the field of product information reuse. At present, some methods utilize the graph theory to excavate structural information, but they are usually complicated. There are also some methods considering the vector collection to get better computing efficiency, but they ignore the connection between parts. Based on the advantages and disadvantages of these methods, this paper proposes an assembly model information quantization method, which integrates structural information into vectorization descriptor and establishes a corresponding index structure and similarity measurement method. First, a connection graph is used to represent the structure features of the assembly, and interconnected part models are divided into several structural units. Then, each structural unit is quantified by the structure-shape distribution function. On this basis, the point set-based assembly descriptor is constructed. Finally, an inverted index and filtering mechanism is established based on the Bag of Word (BOW) algorithm and hypersphere soft allocation strategy. By solving the optimal matching between the query assembly model and the library model, similarity analysis of the assembly model is ultimately realized. © 2021, Beihang University Aerospace Knowledge Press. All right reserved.
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  • [1] ALEMANNI M, DESTEFANIS F, VEZZETTI E., Model-based definition design in the product lifecycle management scenario, The International Journal of Advanced Manufacturing Technology, 52, 1-4, pp. 1-14, (2011)
  • [2] ZHANG B N, QI F R, XING T, Et al., Model based development method of manned spacecraft: Research and practice, Acta Aeronautica et Astronautica Sinica, 41, 7, (2020)
  • [3] ZHANG J, XU Z J, LI Y, Et al., Generic face adjacency graph for automatic common design structure discovery in assembly models, Computer-Aided Design, 45, 8-9, pp. 1138-1151, (2013)
  • [4] DESHMUKH A S, BANERJEE A G, GUPTA S K, Et al., Content-based assembly search: A step towards assembly reuse, Computer-Aided Design, 40, 2, pp. 244-261, (2008)
  • [5] HAN Z P, MO R, YANG H C, Et al., CAD assembly model retrieval based on multi-source semantics information and weighted bipartite graph, Computers in Industry, 96, pp. 54-65, (2018)
  • [6] CHEN X, GAO S M, GUO S, Et al., A flexible assembly retrieval approach for model reuse, Computer-Aided Design, 44, 6, pp. 554-574, (2012)
  • [7] MIURA T, KANAI S., 3D Shape Retrieval considering Assembly Structure: Similarity measure including constraint conditions between components, JSPE Semestrial Meeting, (2009)
  • [8] TAO S Q, WANG S T, ZHENG T G, Et al., CAD model retrieval based on inexact graph matching, Journal of Computer-Aided Design & Computer Graphics, 22, 3, pp. 545-552, (2010)
  • [9] LUPINETTI K, GIANNINI F, MONTI M, Et al., Multi-criteria retrieval of CAD assembly models, Journal of Computational Design and Engineering, 5, 1, pp. 41-53, (2018)
  • [10] SHASHA D, WANG J T L, GIUGNO R., Algorithmics and applications of tree and graph searching, Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART Symposium on Principles of database systems-PODS'02, (2002)
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