基于改进遗传算法的机床主轴径向 回转误差分离技术研究

以提高精密机床主轴回转误差的测量精度为研究目标,基于四点法矩阵算法,采用多圈重合式方法对主轴回转误差测量中的传感器输出数据进行处理。为提高传统遗传算法的收敛速度,降低优化结果对初始值的依赖性,对交叉和变异概率因子列式进行更新,并使用改进遗传算法对传感器安装角度和输出权值系数进行优化。使用改进遗传算法,收敛速率较传统遗传算法提高50%左右。利用多功能斜轨数控车床进行主轴径向回转误差测量及分离实验,分离后的标准芯棒形状误差值与标定值相比,误差在5%以内,且误差重复性低于5%。结果表明分离的结果精度较高,从而验证提出的算法的正确性和可行性。

Research on radial rotation error separation technology of machine tool spindle based on the improved genetic algorithm

To improve the measurement accuracy of the spindle rotation error of precision machine tools, the multi-turn coincidence method is used to process the sensor data in the spindle rotation error measurement, which is based on the four-point matrix algorithm. The convergence speed of the traditional genetic algorithm is improved and the dependence of the optimization results on the initial value is reduced. The crossover and mutation probability factor formulas are updated, and the improved genetic algorithm is used to optimize the sensor installation angle and output weight coefficients. By using the improved genetic algorithm, the convergence rate is about 50% higher than the value of the traditional genetic algorithm. The spindle radial rotation error measurement and separation experiment are implemented by a multifunctional inclined rail CNC lathe. Compared with the calibration value, the deviation of the standard mandrel shape after separation is within 5%, and the error repeatability is less than 5%. Results show that the accuracy of the separation results is high. Thus, the correctness and feasibility of the proposed algorithm are verified.