Abstract
This paper defines static and dynamic component parameters based on the method that converts thrust and torque detected during drilling process into equivalent thrust force and principal force. The features of the parameters are extracted by wavelet packet transform (WPT) and then they are transferred to a back propagation neural network (BPNN) as inputs to predict the drill wear. Experiments with different drilling conditions and workpiece materials were conducted to prove the reliability of this method.
