氮化硅陶瓷轴承外圈磨削的双目标工艺优化

陶瓷轴承套圈的加工质量对轴承的回转精度和服役性能具有重要影响。首先，基于大量外圆磨削试验，通过最小二乘法分别建立陶瓷表面粗糙度和沟道圆度在不同工艺参数下的一元模型；其次，在一元模型基础上，通过粒子群优化算法(PSO算法)分别建立其表面粗糙度和沟道圆度在不同工艺参数下的多元模型；最后，通过PSO算法对表面粗糙度和沟道圆度进行双目标优化，得出轴承外圈加工时的最优工艺参数。结果表明:表面粗糙度在不同工艺参数下的多元复合模型的预测值和实际加工值的相对误差范围为5.83%～8.99%，沟道圆度多元复合模型的预测值和实际加工值的相对误差范围为4.62%～8.01%；双目标函数优化得到的工艺参数为砂轮线速度56.0 m/s、径向进给量0.012 mm/min、工件转速215 r/min。多元模型可较为准确地预测实际加工情况，最优工艺参数下的粗糙度值和圆度值分别为0.130 μm和2.20 μm，相比其他参数下的值较小。 

Two-objective process optimization for grinding of outer ring of silicon nitride ceramic bearing

The machining quality of ceramic bearing rings plays an important role on the rotation accuracy and service performance of the bearing. Firstly, based on a large number of cylindrical grinding experiments, the unitary model of surface roughness with respect to process parameters and the unitary model of raceway roundness with respect to process parameters were established by the least square method. Secondly, on the basis of the unary model, the particle swarm optimization(PSO) algorithm was used to establish a multi-element model of surface roughness with respect to process parameters and a multi-element model of raceway roundness with respect to process parameters. Finally, the surface roughness and raceway roundness are optimized by PSO algorithm. So as to explore the optimal processing parameters of bearing outer ring. The results show that the relative error between the predicted value of the multiple composite model of the surface roughness with respect to the process parameters and the actual processing value is between 5.83% and 8.99%. The relative error between the predicted value of the multivariate composite model of the raceway roundness with respect to the process parameters and the actual processing value is between 4.62% and 8.01%. The process parameters obtained by the dual objective function optimization are the grinding wheel speed of 56.0 m/s, the feed rate of 0.012 mm/min, and the workpiece rotation speed of 215 r/min. Research shows that the multivariate model can predict the actual processing conditions more accurately. The roughness and roundness values under the optimal process parameters are 0.130 μm and 2.20 μm, respectively. Compared with other parameters, it can simultaneously ensure that the roughness and roundness are small.