SVM-based fuzzy modeling for the arc welding process

被引:25
|
作者
Huang, Xixia [1 ]
Chen, Shanben [1 ]
机构
[1] Shanghai Jiao Tong Univ, Welding Engn Inst, Shanghai 200030, Peoples R China
基金
中国国家自然科学基金;
关键词
modeling; fuzzy system; support vector machine; arc welding;
D O I
10.1016/j.msea.2006.04.035
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
This paper proposes a fuzzy modeling method based on support vector machine (SVM) for the arc welding process. SVM provides a mechanism to extract support vectors for generating fuzzy IF-THEN rules from training data. In the proposed SVM-based fuzzy system (SVM-FS), SVM is used to extract EF-THEN rules; the fuzzy basis function inference system is adopted as the fuzzy inference system. So the approach possesses good comprehensibility as well as satisfactory generalization capability. Modeling is one of the key techniques in the automatic control of the arc welding process, and is still a very difficult problem. We give the main steps of modeling for the process using SVM-FS, including selecting input/output variables, acquiring raw data, extracting fuzzy rules and fuzzy inference. Experimental results show that the proposed approach outperforms the rough set method. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:181 / 187
页数:7
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