Gas porosity is very critical factor to affect the welding performance and mechanical properties of weld bead. Dual laser beam welding, as a new laser welding process, is helpful to reduce the porosity number in weld bead because of several advantages like enlarging the molten pool, increasing the fluid speed, stabling the keyhole geometry. However, dual laser beam welding requires consideration of more parameters (beam spacing, energy distribution ratio) than single laser beam welding. To optimize dual beam welding process, a 16 groups Taguchi approach together with artificial neural networks (ANN) and genetic algorithm (GA) has been applied to obtain the best welding parameters of laser beam welding for 316L austenite stainless steel during dual beam laser beam welding. X-ray detection results are regarded as the basis for evaluation of porosity number and welding quality. After optimizing, the porosity number is significantly decreased compared to original weld bead. The comparison of microstructure, and yield strength between original parameters and optimized one is carried out to verify optimal results.

气孔率是影响焊缝焊接性能和机械性能的非常关键的因素。双激光束焊接作为一种新的激光焊接工艺，由于具有增加熔池，增加流体速度，稳定键孔几何形状等多种优点，因此有助于减少焊缝中的气孔数。但是，与单束激光焊接相比，双束激光焊接需要考虑更多的参数（束间距，能量分配比）。为了优化双光束焊接工艺，已应用16组Taguchi方法以及人工神经网络（ANN）和遗传算法（GA）来获得双光束激光束焊接期间316L奥氏体不锈钢激光束焊接的最佳焊接参数。 。X射线检测结果被视为评估孔隙率和焊接质量的基础。优化后，与原始焊缝相比，孔隙率显着降低。比较原始参数和优化参数之间的微观结构和屈服强度，以验证最佳结果。