基于CPSO的点焊工艺参数统计建模和优化  

The Statistical Modeling and Optimization of Spot Welding Process Parameters Based on CPSO

作　　者：刘伟[1,2] 郭猛[1] 

机构地区：[1]东北石油大学电气信息工程学院,黑龙江大庆163318 [2]北京工业大学机械工程与应用电子技术学院,北京100022

出　　处：《组合机床与自动化加工技术》2016年第3期144-147,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家科技重大专项资助项目(2009ZX04014-072)

摘　　要：电阻点焊是多种因素交互作用的复杂过程,点焊熔核直径和高度直接影响电阻点焊焊接强度,点焊熔核直径和高度又受到许多工艺参数的影响。对0.7mm厚AISI1008标准钢板进行点焊实验,在分析点焊焊接工艺的基础上,计全因子实验研究焊接熔核尺寸与焊接工艺参数(焊接时间、焊接电流、焊接压力)之间的关系,同时借助Minitab软件对实验数据进行多元线性回归分析,建立焊接熔核尺寸与焊接工艺参数的统计模型,并对焊接熔核尺寸进行预测。利用混沌粒子群算法(CPSO)对统计模型进行优化,获得最大焊接熔核尺寸下的最优工艺参数搭配。实验结果表明,与正交实验法相比,该方法具有更高的可靠性。Resistance spot welding is a complex process with the interaction of a variety of factors. Welding nugget diameters and heights which is affected by many parameters directly affects the resistance spot weld strength. The spot welding experiments was experimented for 0. 7mm thick AISI1008 steel sheet. Based on the analysis of spot welding process,full factorial experiment was designed to study the relationship between the welding nugget dimension and the welding parameters（ welding time,welding current and welding pressure）. Using Minitab software for multivariate linear regression analysis of the experimental data,the statistical modeling was established of weld nugget size and welding parameters and to predict the weld nugget size. The chaos Particle Swarm Optimization algorithm（ CPSO） was utilized to optimize the statistical modeling and obtained the best parameters match for maximum welding nugget size. Experimental result showthat this method is more reliable compared with orthogonal experimental method.

关 键 词：点焊 全因子试验 CPSO 工艺参数优化 

分 类 号：TH166[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]