Study on the Predictive of Dynamic Milling Force of Milling Process Based on Data Mining

To improve surface accuracy of the work-piece and obtain potentially valuable information, a dynamic milling force prediction model was proposed based on data mining. In view current obtained through finite element simulation analytical calculation, in modeling, built is inevitably different from actual working conditions, calculation slightly cumbersome complex, mining proposed. The established using combination regression analysis Radial Basis Function (RBF) neural network. Using as means, internal relationship between force, cutting parameters, temperature, vibration quality deeply analyzed, influence changes situations extracted summarized by methods cluster correlation analysis. results show that has good effect, ensures production quality, reduces occurrence flutter, improves work-piece, provides more accurate basis for selection process parameters.