Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification

被引:43
|
作者
Qin, Yuchu [1 ]
Lu, Wenlong [1 ]
Qi, Qunfen [2 ]
Liu, Xiaojun [1 ]
Huang, Meifa [3 ]
Scott, Paul J. [2 ]
Jiang, Xiangqian [2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Hubei, Peoples R China
[2] Univ Huddersfield, EPSRC Ctr Innovat Mfg Adv Metrol, Huddersfield HD1 3DH, W Yorkshire, England
[3] Guilin Univ Elect Technol, Sch Mech & Elect Engn, Guilin 541004, Peoples R China
基金
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词
Computer-aided tolerance specification; Tolerance specification scheme; Tolerance specification problem; Case-based reasoning; Ontology; Similarity measure; SEMANTIC SIMILARITY; PRODUCT; SYSTEM;
D O I
10.1016/j.knosys.2017.11.013
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an ontology-supported case-based reasoning approach for computer-aided tolerance specification is proposed. This approach firstly considers the past tolerance specification problems and their schemes as previous cases and the new tolerance specification problems as target cases and uses an ontology to represent previous and target cases. Then certain ontology-based similarity measure is used to assess the similarity between the toleranced features of target and previous cases, the similarity between the part features of target and previous cases, and the similarity between the topological relations of target and previous cases. Based on these similarities, an ontology-based similarity measure for computing the similarity between target and previous cases is designed, and an algorithm for establishing such similarity measure with high accuracy and retrieving similar previous cases for a target case with this similarity measure is presented. This algorithm shows how to linearly combine the similarity of toleranced features, the similarity of part features, and the similarity of topological relations to assess the similarity between target and previous cases to implement retrieval of previous cases under the prerequisite of ensuring the highest accuracy of the similarity measure. The paper also reports a prototype implementation of the proposed approach, provides an example to illustrate how the approach works, and evaluates the approach via theoretical and experimental comparisons. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:129 / 147
页数:19
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