基于RSM与NSGA-Ⅱ算法的激光熔覆参数多目标优化

Multi-Objective Optimization of Laser Cladding Parameters Based on RSM and NSGA-Ⅱ Algorithm

为了获得激光熔覆FeCrNiSi粉末在Q690上的最佳工艺参数,提出了一种基于响应面法(RSM)与第二代非支配排序遗传算法(NSGA-Ⅱ)的激光熔覆参数优化方法。通过设计响应面法中的Box-Benhnken试验方案,搭建输入变量(激光功率、扫描速度、送粉速率)与响应值(稀释率、热影响区深度、显微硬度)之间的代理模型,运用NSGA-Ⅱ对工艺参数进行寻优,结果表明,激光功率为1950 W,扫描速度为19 mm/s,送粉速率为2.4 r/min时,获得最优参数,在此条件下熔覆后的试件的稀释率降低了22.4%,热影响区深度减小了17.9%,显微硬度增大了4.2%。

In order to obtain the best technological parameters of laser cladding FeCrNiSi powder on Q690,an optimization method of laser cladding parameters based on response surface method(RSM) and second generation non-dominated sorting genetic algorithm(NSGA-Ⅱ) algorithm is proposed.By designing the Box-Benhnken experiment scheme in response surface method,the proxy model between the input variables(laser power,scanning speed,and powder feeding rate) and the response values(dilution,heat affected zone depth,and microhardness) is established,and the process parameters were optimized by NSGA-Ⅱ.The results show that the optimal parameters are obtained when the laser power is 1950 W,the scanning speed is 19 mm/s,and the powder feeding rate is 2.4 r/min.Under these conditions,the dilution rate of the cladding specimen decreases by 22.4%,the depth of the heat affected zone decreases by 17.9%,and the microhardness increases by 4.2%.