软轴摩擦力计算公式的结构参数优化设计  

The structure parameter optimization design of soft shaft friction empirical formula

作　　者：李健[1] 张宝[1] 徐敏[1] 李尽力 LI Jian ZHANG Bao XU Min LI Jin-li(School of Mechanical Engineering, Guangxi University of Science and Technology, Liuzhou 545006, Chin)

机构地区：[1]广西科技大学机械工程学院,广西柳州545006

出　　处：《广西科技大学学报》2016年第3期21-25,共5页Journal of Guangxi University of Science and Technology

基　　金：广西科学研究与技术开发计划项目(10100026)资助

摘　　要：通过最小二乘回归分析方法推导出软轴摩擦力计算公式,并运用粒子群算法对其进行修正.修正后的软轴摩擦力计算经验公式可以有很多方面的应用.本文运用遗传算法结合该经验公式及某些约束条件对软轴摩擦力大小进行优化,得出最小摩擦力出现时软轴的几何参数.结果表明:在限定极限弯曲挠度的条件下,出现软轴摩擦力极小值时的芯轴长度及弯曲半径均取在所规定的取值边界上,而芯轴直径随着极限弯曲挠度的增大而减小.Soft shaft friction empirical formula is deducted by least-squares regression analysis method, then it is corrected by particle swarm optimization. The corrected empirical formula for calculating the shaft friction can be applied in many aspects. For example, the friction force can be calculated by putting three numerical values of the shape parameters into the empirical formula. The article attempts to use the genetic algorithm combined with the empirical formula and some constraints on the soft shaft friction optimization, then it obtains the geometric parameters of soft shaft as the minimum friction appears. The results show that： under the condition of limited maximum bending deflection, the minimal value of soft shaft friction appears when core shaft length and bending radius are specified in the values on the border. But the spindle diameter decreases with the increase of the limit bending deflection.

关 键 词：软轴 摩擦力 经验公式 遗传算法 

分 类 号：TH117.1[机械工程—机械设计及理论]