Burns prediction of TC4-Ti-alloy based on scaled conjugate gradient neutral networks

In order to predict the degree of TC4 titanium alloy after high-speed cylindrical grinding,surface hardness is used to differentiate grinding burns of the workpiece based on surface hardness value change resulted by phase transformation after grinding burn.Surface hardness of TC4 titanium alloy after high-speed cylindrical grinding is forecasted using the scaled conjugate gradient algorithm of neural network.Correspondence relationship between the surface hardness value and the degree of grinding burn is used to predict grinding burns.Validation experiment indicates that the error between the experiments and the predictions is within 5%,which means that the model prediction effect is good.