基于逐步回归分析法的表面粗糙度预测

为减少渗碳钢轴的导磁性对磁粒研磨加工的影响，将磨料贮存于周围镶嵌多个磁极的圆形容器中，使被工件带走的磁性粒子能够在磁极间循环利用，虽然降低了磁性磨料在单个磁极处的自我更新作用，但是能够防止磁性磨料的流失。开展对20CrMnTi材质的轴类零件的试验，以加工时间、工件转速、磁性磨料和研磨液的质量比、磁性磨粒的粒径为自变量，工件表面粗糙度作为因变量，采用逐步回归分析建立表面粗糙度预测模型，通过试验验证预测结果的准确性。结果表明:预测模型的表面粗糙度的相对误差绝对值能够控制在7%以内，具有较好的预测能力。 

Surface roughness prediction based on stepwise regression analysis

To reduce the magnetic resistance of the carbon steel shaft on the method of processing the carbon steel shaft of the magnetic particles, the abrasive is stored in a circular vessel in which a plurality of magnetic poles is contained, and the magnetic particles taken away by the workpiece can be in the magnetic pole for cyclic utilization. Although the self-update of magnetic abrasive is in a single magnetic pole, it is possible to prevent the loss of magnetic abrasives. Further, in the test of the axial part of the 20CrMnTi material, the particle size of the magnetic abrasive particles is independent variable with the mass ratio of the machining time, the workpiece rotation speed, the magnetic abrasive and the polishing liquid, and the surface roughness as the dependent variable. The prediction model of surface roughness is established by stepwise regression analysis. The accuracy of the prediction result is found through the test, and it is found that the absolute value of relative error of surface roughness can be controlled within 7%, which has good prediction ability.