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介绍了一种利用回归分析法来建立单点金刚石刀具超精车削表面粗糙度预测模型的新方法 ,并通过建立的粗糙度预测模型 ,研究了铝合金超精密车削过程中切削速度、进给量和切削深度等参数对表面粗糙度的影响。通过实验分析表明 :二次预测方程比一次预测方程更有效 ,而且适用范围比一次模型大。利用优化设计中的约束变尺度法对所建立的表面粗糙度预测方程进行了优化 ,可以实现对切削参数的优选 ,从而达到加工前在特定的条件下预测和控制表面粗糙度的目的。
A new method of using regression analysis to build a single-point diamond tool super-precision turning surface roughness prediction model is introduced. Through the established roughness prediction model, the effects of cutting speed, feed rate And cutting depth and other parameters on the surface roughness. The experimental results show that the quadratic prediction equation is more effective than the one-time prediction equation, and its application range is larger than the one-time model. By using constrained variable-scale method in optimization design, the established prediction equation of surface roughness is optimized, which can optimize the cutting parameters and achieve the purpose of predicting and controlling the surface roughness under certain conditions before machining.