基于RBF神经网络的难加工材料高速铣削粗糙度预报研究

Prediction of Surface Roughness of Difficult-to-cut Material by HSM Based on RBF Neural Network

表面粗糙度的预报是切削加工质量分析的重要研究方向。本文运用RBF神经网络建立了粗糙度预测模型,将预报结果与试验真值以及由经验公式的处理结果进行对比验证,结果表明此方法可行,为切削参数优化和数据库研制提供了依据。

Prediction of surface roughness has become an important trend of cutting quality analysis. In this paper, RBF neural network is used to establish the prediction model of surface roughness. Compared with measured data and data from regression analysis, the result of prediction using RBF neural network indicates its feasibility, which provides reference for the optimization of cutting parameters and the development of database.