Optimisation of hybrid tandem metal active gas welding using Gaussian process regression

被引:14
|
作者
Lee, Dae Young [1 ]
Leifsson, Leifur [1 ]
Kim, Jin-Young [2 ]
Lee, Seung Hwan [2 ]
机构
[1] Iowa State Univ, Ames, IA USA
[2] Korea Aerosp Univ, 76 Hanggongdae Gil, Goyang Si 10540, Gyeonggi Do, South Korea
关键词
Tandem flux cored arc welding; hot-wire; hybrid tandem metal active gas welding; Gaussian process regression; parameter optimisation; fillet welding; machine learning; PARAMETER OPTIMIZATION; PREDICTION;
D O I
10.1080/13621718.2019.1666222
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, an additional filler wire with opposite polarity was inserted in tandem flux cored arc welding process to increase the welding speed and deposition rate. In this hybrid welding, the optimisation of welding parameters is required to improve the bead geometry which directly indicates the welding quality. However, the correlation between the parameters and the bead geometry is hard to identify, so the process parameters are usually selected intuitively by the experienced engineers. Therefore, welding process modelling is constructed with the Gaussian process regression model, and parameter optimisation is performed with sequential quadratic programming optimisation algorithm. The proposed modelling optimisation process is verified by performing the welding experiment using the parameters that are optimised by the proposed process.
引用
收藏
页码:208 / 217
页数:10
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