An investigation into an intelligent system for predicting bead geometry in GMA welding process

In this paper, we develop an intelligent system in GMA welding processes using MATLAB/SIMULINK software. Based on multiple regressions and a neural network, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. Graphic displays represent the resulting solution on the bead geometry that can be employed to further probe the model. The developed system enables to input the desired weld dimensions and select the optimal welding parameters. The experimental results were proved the capability of the developed system to select the welding parameters in GMA welding process according to complex external and internal geometrical features of the substrate.