Nonlinear Multiple Regression Modeling of Weld Bonding for DP780 High Strength Steel

Based on the Box-Behnken Design (BBD) method, the experiment on weld bonding for DP780 high-strength steel was carried out. The fai-lure load of the joints and the diameter of the nugget were viewed as the target quantity. The welding current, welding time, electrode pressure and the interaction between the parameters were defined as the factors to influence the target quantity. The nonlinear multiple regression modeling of the weld-bonded joints for DP780 high strength steel was established. The experimental verification shows that the model has high saliency and high degree of fitting, which can effectively predict the joints failure load and nugget diameter. With the increase of welding current and the welding time, the failure load of the weld-bonded joints and the diameter of the nugget increase, while they decrease with the increase of electrode pressure. The optimal process parameters were welding current 8.3 kA, welding time 150 ms, electrode pressure 0.3 MPa, which were obtained by the regression model, and the joint's failure load under the shear test was 16 369 N. The ultrasonic C-scan image was used to identify the gasification zone of the adhesive layer outside the weld nugget. When the welding time is small, the increase of the welding current will provide more heat input, which will lead to an increase in the burning area of the adhesive layer and reduce the static properties of the joints. © 2020, Materials Review Magazine. All right reserved.