Residual tensile stresses generated during butt welding of plates using arc welding process lead to deformation and deterioration of fatigue strength of welded parts. This research implemented particle swarm optimization (PSO) algorithm to present optimum welding parameters to minimize the tensile residual stresses of butt-welded 304 stainless-steel plates with 4–15 mm thicknesses. A set of 32 experiments was designed using Taguchi method and simulated using ABAQUS commercial software based on element birth-and-death finite element technique. An artificial neural network and PSO were utilized to discover the optimum welding settings. To ensure the accuracy of simulation results, slitting method was implemented to measure residual stresses utilizing digital image correlation technique beside the strain gauges.

采用弧焊工艺对板材进行对接焊时产生的残余拉应力会导致焊接件的变形和疲劳强度劣化。本研究采用粒子群优化 (PSO) 算法来呈现最佳焊接参数，以最大限度地减少对接焊 4-15 毫米厚度的 304 不锈钢板的拉伸残余应力。使用田口法设计了一组32个实验，并基于单元生死有限元技术使用ABAQUS商业软件进行模拟。利用人工神经网络和 PSO 来发现最佳焊接设置。为保证仿真结果的准确性，在应变片旁采用数字图像相关技术，采用切缝法测量残余应力。