回归分析在超精密加工表面粗糙度预测中的应用

Application of Regression Analysis Method in Ultra-precision Machining Surface Roughness Prediction

由于采用传统的研磨和抛光方法很难将KDP这样的软脆单晶材料加工出超光滑的表面,因此,国内外目前多采用单点金刚石切削的方式。为了实现切削参数优选以及达到加工前对加工表面质量进行预测和控制的目的,本文除了采用回归分析的方法建立了KDP晶体超精密切削加工表面粗糙度的预测模型外,还通过优化设计软件对模型切削参数进行了优化。经过实验结果表明,采用回归分析方法建立的KDP晶体超精密切削加工表面粗糙度的预测模型是可靠有效的。

It is difficult to work out super smooth surface for soft brittle crystal materials like KDP with traditional grinding and polishing methods, so single point diamond cutting method is commonly used at home and abroad. In order to realize the optimization of cutting parameters and machining surface quality prediction and control to achieve the purpose of processing, in addition to a KDP crystal in ultra precision machined surface roughness prediction model by regression analysis method, the optimization design software to optimize the cutting parameters model. The experimental results show that, by using the regression analysis method to establish KDP crystal ultra precision machined surface roughness prediction model is reliable and effective.