外圆纵向磨削表面粗糙度的模糊预测与控制

在大量实验数据和专家经验基础上,建立了外圆纵向磨削零件表面粗糙度Ra的模糊预测和模糊控制模型。对影响表面粗糙度的12个主要变量进行了深入研究,并对其中的7个主要变量的成员函数和模糊规则进行了详细介绍。该模型能根据磨削条件和工件参数的变化,不断地调整磨削参数。将所得结果输入到模糊自适应控制器中,系统即可实时调整工件转速,得到符合要求的表面粗糙度。试验结果表明:表面粗糙度的模糊预测和控制方法非常有效,可操作性强,尤其适用于非线性、多变量的工况。

Surface Roughness Prediction and Control of Cylinder Traverse Grinding Based on Fuzzy Logic

A fuzzy prediction and control model for the surface roughness of cylinder traverse grinding was developed based on the experimental data and the expertise. A total of 12 variables which have effect on the grinding surface roughness were included, and the membership functions of the 7 major variables of them and their fuzzy rules were presented. The model can adjust the grinding parameters according to the variation of the grinding conditions and the workpiece parameters. Input of the model outputs into a fuzzy adaptive controller leads to the system to adjust real-timely the workpiece speed, getting the up to the requirements surface roughness. The experimental results showed that the developed fuzzy prediction and control model for the surface roughness is simple, effective and practical, and especially good for the non-linear and multivariable conditions.