基于IDBO-BP与PSO的超声冲击薄板激光焊接残余应力预测与工艺优化  

Residual stress prediction and process optimization of ultrasonic impact treatment for laser welding sheet based on IDBO-BP and PSO

作　　者：薛欢 张洛源 张文谦 徐赛清 彭萧剑 郭畅 苏子傲 XUE Huan;ZHANG Luoyuan;ZHANG Wenqian;XU Saiqing;PENG Xiaojian;GUO Chang;SU Ziao(School of Mechanical Engineering,Hubei University of Technology,Wuhan 430068,China;Key Lab of Modern Manufacture Quality Engineering,Wuhan 430068,China;Wuhan Dehua Testing Engineering Co.,LTD.,Wuhan 430068,China)

机构地区：[1]湖北工业大学机械工程学院,武汉430068 [2]现代制造质量工程重点实验室,武汉430068 [3]武汉市德华测试工程有限公司,武汉430068

出　　处：《现代制造工程》2025年第3期9-18,共10页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(52205148)。

摘　　要：45Mn薄板在激光焊接过程中产生的残余拉应力,将对其强度、韧性以及疲劳寿命产生不利的影响。采用多种超声冲击工艺对薄板表面进行强化,并提出一种对薄板超声冲击工艺参数的多目标优化方法。首先,通过有限元冲击仿真得到了不同冲击工艺参数下薄板表面残余应力的数据集;然后,以仿真数据集为基础,采用IDBO-BP神经网络成功建立了冲击工艺参数与表面残余应力之间的非线性映射关系。通过IDBO-BP神经网络与BP、GA-BP、PSO-BP和DBO-BP等神经网络对比,发现IDBO-BP神经网络预测薄板表面残余应力的精度更高,MAE和R 2这2种评价指标分别为0.0683和0.9974,表明该模型可以有效地预测超声冲击薄板后的残余应力;最后,以超声冲击工艺参数为设计变量,以最小残余应力、最小冲击电流和最小冲击时间为优化目标,结合IDBO-BP神经网络和PSO算法,得到与超声冲击工艺参数对应的残余应力、冲击电流和冲击时间Pareto最优解集。结果显示,优化后的冲击工艺有效提高了加工效率和加工能效。The residual tensile stress generated during the processing operations of laser welding in 45Mn sheet has adverse effects on their strength,toughness,and fatigue life.Various ultrasonic impact processes were employed to enhance the surface of the sheet and a multi-objective optimization method for the ultrasonic impact process parameters of sheet was proposed.Firstly,a dataset of surface residual stress under different impact process parameters was obtained through finite element impact simulation.Then,based on the simulation dataset,a nonlinear mapping relationship between impact process parameters and surface residual stress was successfully established using the IDBO-BP neural network.Comparing the IDBO-BP neural network with BP,GA-BP,PSO-BP,and DBO-BP neural networks,it was found that the IDBO-BP neural network achieves higher accuracy in predicting surface residual stress of the sheet,with MAE and R 2 evaluation metrics reaching 0.0683 and 0.9974,respectively,indicating the effectiveness of the model in predicting residual stress after ultrasonic impact.Finally,considering the ultrasonic impact process parameters as design variables and aiming for minimal residual stress,minimal impact current,and minimal impact time,a Pareto optimal solution set of residual stress,impact current,and impact time corresponding to the ultrasonic impact process parameters was obtained by combining the IDBO-BP neural network and the PSO algorithm.The results demonstrate that the optimized impact process effectively improves processing efficiency and processing energy efficiency.

关 键 词：45Mn 超声冲击 改进蜣螂优化算法 残余应力 多目标优化 

分 类 号：TG663[金属学及工艺—金属切削加工及机床]