基于MIGA的超声振动滚(挤)压加工工艺参数优化  

Optimization of ultrasonic vibration rolling(extrusion)process parameters based on MIGA

作　　者：刘玲玲[1,2,3] 付浩然 LIU Ling-ling;FU Hao-ran(School of Intelligent Engineering,Zhengzhou College of Finance and Economics,Zhengzhou 450000,China;Zhengzhou Key Laboratory of Intelligent Assembly Manufacturing and Logistics Optimization,Zhengzhou 450000,China;Henan Engineering Technology Research Center of Intelligent Cold Chain Logistics Equipment Manufacturing,Zhengzhou 450000,China;College of Mechanical and Electrical Engineering,Henan University of Science and Technology,Luoyang 471003,China)

机构地区：[1]郑州财经学院智能工程学院,河南郑州450000 [2]郑州市智能装配制造与物流优化重点实验室,河南郑州450000 [3]河南省智能冷链物流装备制造工程技术研究中心,河南郑州450000 [4]河南科技大学机电工程学院,河南洛阳471003

出　　处：《塑性工程学报》2024年第12期18-25,共8页Journal of Plasticity Engineering

基　　金：河南省科技攻关项目(242102221005,222102210202);河南省本科高校青年骨干教师培养计划(2024GGJS179);河南省高等学校重点科研项目(22A460028)。

摘　　要：为提高轴承的综合表面性能,实现超声振动滚(挤)压加工工艺参数的优化控制,基于超声振动滚(挤)压加工原理展开运动学分析,并进行四因素五水平的正交试验,采用方差分析的方法分析影响表面性能的显著性因素:静压力对表面粗糙度和残余应力的影响最大,振幅对硬度的贡献率最大;采用响应曲面法确定了工艺参数与表面性能之间的多元回归预测模型,经检验表面性能的调整系数R-sq与调整相关系数R-sq(adj)均在95%以上,说明了预测模型的准确性;基于MIGA对表面性能的数学模型进行多目标优化,得到最优加工参数域:转速[140,180]r·min^(-1)、进给速度[15,19]mm·min^(-1)、振幅[20,25]μm、静压力[530,600]N,表面性能参数域:表面粗糙度[0.428,0.450]μm、残余应力[-1270,-1220]MPa、硬化程度[108.8%,116.3%],实现了多目标优化的全局最优。To improve the comprehensive surface performance of bearings and achieve optimization control of ultrasonic vibration rolling(extrusion)parameters,the kinematic analysis was carried out based on the principle of ultrasonic vibration rolling(extrusion)machi-ning,and the orthogonal tests of four factors and five levels were carried out.The method of variance analysis was used to identify the sig-nificant factors affecting surface performance:static pressure has the greatest impact on surface roughness and residual stress,and ampli-tude has the greatest contribution to hardness.The response surface method was used to determine the multiple regression prediction model between process parameters and surface performance.After testing,the adjustment coefficients R-sq and correlation coefficients R-sq(adj)of surface performance were both above 95%,indicating the accuracy of the prediction model.Based on the MIGA,a multi-objective optimi-zation was performed on the mathematical model of surface performance,obtaining the optimal machining parameter domains:rotation speed of[140,180]r·min^(-1),feed rate of[15,19]mm·min^(-1),amplitude of[20,25]μm,static pressure of[530,600]N,and surface performance parameters domains:surface roughness of[0.428,0.450]μm,residual stress of[-1270,-1220]MPa,and hardening degree of[108.8%,116.3%],achieving the global optimization of multi-objective optimization.

关 键 词：超声振动 方差分析 多元回归 预测模型 

分 类 号：TG376.1[金属学及工艺—金属压力加工]