Research and Analysis on Prediction of Welding Deformation of Flange Plate of Loading Wheel

Welding deformation prediction predicts the deformation that may occur during the welding process, the corresponding measures can be taken to control the deformation. In this paper, the finite element analysis software is used to simulate the welding process of the load wheel flange plate of the special vehicle body. Based on the finite element analysis method, the welding deformation data set under different welding voltage, welding current and welding speed is obtained. The process parameters of orthogonal experimental design are used for welding, and the deformation of the flange plate of the loading wheel after welding is measured by three- dimensional laser scanner. The welding deformation simulation results are in good agreement with the experimental results, so the finite element simulation method in this paper can better reflect the actual welding deformation. In order to improve the efficiency and accuracy of welding deformation prediction, a deformation prediction model based on improved genetic algorithm optimized BP neural network (improved GA-BP) is proposed. Finally, the improved GA-BP algorithm model is used to verify the engineering verification of the flange plate of the load wheel obtained by the welding experiment. Based on the improved GA-BP neural network, the error between the predicted value of the welding deformation and the average value of the experimental measurement is within 9%, and the predicted value is consistent with the experimental measurement value. The application value of the improved GA-BP neural network in engineering is verified.