Modeling, optimization and classification of weld quality in tungsten inert gas welding

被引：73

作者：

Tarng, YS ^{[1
]}

Tsai, HL ^{[1
]}

Yeh, SS ^{[1
]}

机构：

[1] Natl Taiwan Inst Technol, Dept Mech Engn, Taipei 10672, Taiwan

来源：

INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE | 1999年 / 39卷 / 09期

关键词：

modeling; optimization; FUZZY clustering; weld quality;

D O I：

10.1016/S0890-6955(99)00013-9

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, a neural network is used to construct the relationships between welding process parameters and weld pool geometry in tungsten inert gas (TIG) welding. An optimization algorithm called simulated annealing (SA) is then applied to the network for searching the process parameters with an optimal weld pool geometry. Finally, the quality of aluminum welds based on the weld pool geometry is classified and verified by a fuzzy clustering technique. Experimental results are presented to explain the proposed approach. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：1427 / 1438

页数：12

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