Artificial neural network application to the friction-stir welding of aluminum plates

被引:193
|
作者
Okuyucu, Hasan
Kurt, Adem [1 ]
Arcaklioglu, Erol
机构
[1] Gazi Univ, Fac Tech Educ, TR-06500 Ankara, Turkey
[2] Kirikkale Univ, Dept Mech Engn, TR-71450 Kirikkale, Turkey
关键词
friction stir welding; mechanical properties; ANN; modeling;
D O I
10.1016/j.matdes.2005.06.003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An artificial neural network (ANN) model was developed for the analysis and simulation of the correlation between the friction stir welding (FSW) parameters of aluminium (Al) plates and mechanical properties. The input parameters of the model consist of weld speed and tool rotation speed (TRS). The outputs of the ANN model include property parameters namely: tensile strength, yield strength, elongation, hardness of weld metal and hardness of heat effected zone (HAZ). Good performance of the ANN model was achieved. The model can be used to calculate mechanical properties of welded Al plates as functions of weld speed and TRS. The combined influence of weld speed and TRS on the mechanical properties of welded Al plates was simulated. A comparison was made between measured and calculated data. The calculated results were in good agreement with measured data. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:78 / 84
页数:7
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