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J. Ha(하정홍),J. W. Kim(김재원),H. Jun(전현욱),D.-H. Kim(김동현),S.-H. Lee(이성호),C. Ji(지창욱) Korean Society for Precision Engineering 2021 한국정밀공학회 학술발표대회 논문집 Vol.2021 No.11월
9% Nickel steel is spotlighted as a promising material for LNG tanks due to its advantages of high yield strength, high tensile strength, and excellent impact resistance in a cryogenic environment. Laser beam welding is one of the promising technologies for welding of 9% nickel steel due to its advantages including no arc deflection, high weld quality, and easy automation. In this study, a model for predicting laser welding penetration depth of 9% nickel steel was developed using multiple regression methods. The laser welding process was performed by adjusting the process parameters, and the penetration depth was measured for each process condition. Datasets were constructed based on the experimental results and a predictive model based on multiple regression was developed. For linear regression and second-order polynomial regression models, the optimal feature combination was selected using exhaustive feature selector. The prediction model was trained with the optimal feature combination using cross validation technique, and the penetration depth was predicted according to the process parameters.