摘要
针对现有铣削加工工艺材料利用率和加工效率低下,且加工工件表面粗糙度达不到质量要求的问题,本研究以2195铝锂合金薄壁构件铣削加工工艺为研究对象,基于改进PSO算法,对其加工工艺参数进行多目标参数优化。首先,研究以材料去除率和表面粗糙度为优化目标,以主轴转速、每齿进给量、轴向切深、径向切深为优化变量,以优化变量的参数范围、数控铣床性能参数等为约束条件,采用改进PSO算法对其进行优化;然后,采用灰色关联度分析法计算求解目标函数权重系数最优解;最后,通过仿真实验验证最优解的可行性和准确性。结果表明,采用改进PSO算法优化后的铣削加工工艺参数,可在保证铣削加工工件质量的同时,最大程度提高加工效率。
In view of the low material utilization and processing efficiency of the existing milling process,and the surface roughness of the workpiece can not meet the quality requirements,this study takes the milling process of 2195 aluminum lithium alloy thin-walled components as the research object,and based on the improved PSO algorithm,the multi-objective parameter optimization of its processing parameters is carried out.Firstly,taking the surface roughness and material removal rate as the optimization objectives,taking the spindle speed,feed per tooth,axial cutting depth and radial cutting depth as optimization variables,and taking the parameter range of optimization variables and performance parameters of CNC milling machine as constraint conditions,the improved PSO algorithm is used to optimize the optimization;then,the weight coefficient of the objective function is calculated by grey correlation analysis method Finally,the feasibility and accuracy of the optimal solution are verified by simulation experiments.The results show that the milling process parameters optimized by improved PSO algorithm can ensure the quality of milling workpiece and improve the processing efficiency to the greatest extent.
作者
郭长城
GUO Chang-cheng(Jianghai Polytechnic College,School of Mechanical and Electrical Automobile,Yangzhou 225101,China)
出处
《内燃机与配件》
2021年第22期21-25,共5页
Internal Combustion Engine & Parts
基金
江苏高校哲学社会科学研究项目,“基于OBE理念下思政元素融入《数控编程与操作》课程教学的实践研究”,项目编号:2021SJA2013。
关键词
铣削工艺
参数优化
PSO算法
灰色关联度分析法
milling process
parameter optimization
PSO algorithm
grey correlation analysis method
