Process and Parameter Optimization of the Double-Pulsed GMAW Process

Abstract

The double pulsed gas metal arc welding (DP-GMAW) process has been effectively employed to realize joining of steel plates and obtain weld bead surfaces with high quality fish scale ripples. In this work, a DP-GMAW process based on robot operation using the latest twinpulse XT DP control technology was employed to join the stainless-steel base plates. Four key operational parameters, which were robot welding speed, twin pulse frequency, twin pulse relation and twin pulse current change in percent, were selected to be input elements of orthogonal experimental design, which included nine experiments with three levels. To accurately understand the performance and process of weld bead obtained from DP-GMAW operation based on robot operation, the appearance observation and key shape parameters measurement, microstructure analysis, tensile and hardness testing, as well as stability analysis of the electrical signals, were conducted. Correlation analysis showed that the grain size was significantly correlative to the toughness and hardness. Then, to obtain quantitative evaluation results, fuzzy comprehensive evaluation (FCE) was employed to provide quality evaluation of weld beads from the above experiments. The influential levels of the key operational parameters on the appearance, grain size and FCE scores, and corresponding physical analyses, were respectively presented. In addition, optimal parameters combinations for obtaining weld beads with optimal appearance, grain size, and the highest FCE scores of weld bead quality were respectively provided according to the range analysis of the results from orthogonal experimental design. This work can provide an effective analysis method of influential levels of key operational parameters on the performance of the weld bead, optimal operational parameters combination seeking method, and quantitative quality evaluation method for the DP-GMAW process, which can improve the process optimization and increase the production efficiency, both in academic research and actual industrial production.