基于遗传算法的二并联机床钻尖刃磨参数优化

Optimization of Grinding Parameters for Drill Points with a Biglide Parallel Machine Based on Genetic Algorithm

以螺旋面钻尖刃磨为研究对象,基于二并联机床优化磨削参数,为实现所需的几何参数螺旋面钻尖刃磨提供理论与实验基础.介绍了基于二并联机床的渐开螺旋面刃磨方法,针对螺旋面钻尖后刀面推导了数学模型.分析了二并联机床的磨削参数与螺旋面钻尖几何参数的关系,然后用遗传算法得出螺旋面钻尖刃磨参数优化解.在二并联机床上进行刃磨实验,结果表明,采用本文的优化刃磨参数提高了刃磨精度,并验证用二并联机床可以刃磨出满足用户几何参数要求的螺旋面钻尖.

In view of helical drill point grinding, the theoretical and experimental bases for grinding the required geometrical parameters of helical drill points are presented in this paper based on the optimization of biglide parallel machine grinding parameters. A method of grinding the involute helical surface based on the biglide parallel machine is introduced, and then the mathematical model is derived for the helical drill flank. Moreover, the relationship between the geometric parameters and grinding parameters is analyzed, and the optimal grinding parameters are acquired based on genetic algorithm. The results showed that the optimized grinding parameters improve the grinding precision with the experiment on the biglide parallel machine, and the biglide parallel machine can satisfy clients＇ demands of drill grinding.