摘要
为了准确辨识得到球头铣刀切削刃存在差异的切削力系数,提出结合平均铣削力方法和粒子群优化算法的辨识方法.首先,建立球头铣刀的铣削力模型,推导基于平均铣削力且忽略切削刃差异的切削力系数辨识模型.然后,以基于平均铣削力方法辨识得到的切削力系数为初值、最小化铣削力仿真结果和测量结果的偏差平方和为目标,引入修正系数为设计变量,设计基于粒子群优化的切削力系数修正算法.最后,进行仿真和实验验证,相关结果表明采用修正后的切削力系数不仅能准确地预测切削刃存在差异的铣削力峰值,而且具有更好的吻合度和精度.
In order to determine cutting force coefficients of a ball-end milling cutter, in which cutting edges have differences, a new method combining the average milling force method with particle swarm optimization(PSO)was proposed.Firstly, the milling force models and the identification models based on the average milling force method are constructed ignoring the differences of cutting edges.Then, the algorithm for searching more accurate cutting force coefficients based on PSO was given.The algorithm uses the coefficients obtained by the average milling force method as initial values, correction factors of cutting force coefficients as design parameters, and sum of squared deviations between the minimum cutting force of simulation and experiment as objective function.Finally, a series of simulations and experiments are performed.The results show that the predicted milling forces with corrected cutting force coefficients have a better consistency with measured forces.
作者
黎柏春
王振宇
张斌
王宛山
LI Bai-chun;WANG Zhen-yu;ZHANG Bin;WANG Wan-shan(School of Mechanical Engineering & Automation,Northeastern University,Shenyang 110819,China;School of Computer Science & Engineering,Northeastern University,Shenyang 110169,China)
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2019年第9期1316-1322,共7页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金青年基金资助项目(51505072)
中央高校基本科研业务费专项资金资助项目(N160303001,N150306001,N182303034)
关键词
球头铣刀
切削力系数
铣削力
系数辨识
粒子群优化
ball-end milling cutter
cutting force coefficients
milling forces
coefficient identification
particleswarm optimization(PSO)