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Cited 5 time in webofscience Cited 5 time in scopus
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Optimisation of hybrid tandem metal active gas welding using Gaussian process regression

Authors
Lee, Dae YoungLeifsson, LeifurKim, Jin-YoungLee, Seung Hwan
Issue Date
Apr-2020
Publisher
TAYLOR & FRANCIS LTD
Keywords
Tandem flux cored arc welding; hot-wire; hybrid tandem metal active gas welding; Gaussian process regression; parameter optimisation; fillet welding; machine learning
Citation
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING, v.25, no.3, pp.208 - 217
Indexed
SCIE
SCOPUS
Journal Title
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING
Volume
25
Number
3
Start Page
208
End Page
217
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2589
DOI
10.1080/13621718.2019.1666222
ISSN
1362-1718
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.
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COLLEGE OF ENGINEERING (SCHOOL OF MECHANICAL ENGINEERING)
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