Accurate Prediction of the Weld Bead Characteristic in Laser Keyhole Welding Based on the Stochastic Kriging Model

As an important index of weld quality, the weld bead geometry is closely related to the welding process parameters (WPP). Therefore, it is crucial to establish the relationships between the WPP and weld bead shape to serve as an indicator of the weld quality. However, it is difficult to predict the weld bead shape accurately due to uncertainty. In this paper, laser keyhole welding (LKW) experiments are conducted on 2205 stainless steel at sample points generated by the optimal Latin hypercube sampling (OLHS). Then the relationships between WPP and weld width (WW) are constructed using stochastic kriging model (SKM), considering the randomness of the welding process. To verify the effectiveness of the SKM, two validation approaches, the additional experiments validation and k-fold cross-validation, are used to compare the prediction performance of SKM and the traditional kriging model. SKM is superior to the kriging model at the whole five additional test points with smaller relative error. As to k-fold cross-validation, SKM provides a smaller root mean square error at four in five groups of the data. In addition, SKM can provide the variations of the entire weld bead shape. Overall, the SKM is very prominent in predicting the weld bead shape, considering fluctuations of WPP.