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

Title
Optimisation of hybrid tandem metal active gas welding using Gaussian process regression
Author
이승환
Keywords
Tandem flux cored arc welding; hot-wire; hybrid tandem metal active gas welding; Gaussian process regression; parameter optimisation; fillet welding; machine learning
Issue Date
2019-09
Publisher
TAYLOR & FRANCIS LTD
Citation
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING, v. 25, no. 3, Page. 208-217
Abstract
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.
URI
https://www.tandfonline.com/doi/full/10.1080/13621718.2019.1666222https://repository.hanyang.ac.kr/handle/20.500.11754/153905
ISSN
1362-1718; 1743-2936
DOI
10.1080/13621718.2019.1666222
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > MECHANICAL ENGINEERING(기계공학부) > Articles
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