Research on tool wear monitoring of aero-engine parts machining

摘要

This paper presents a tool wear monitoring method which can be applied to high-precision aero-engine parts machining. The degree of tool wear during machining is closely related to the machining accuracy. Effective state monitoring can ensure machining accuracy and provide guidelines to change tools. This paper put forward a new analysis method and monitoring program using signal of vibration and sound pressure. The process data are obtained by milling experiment. On the basis of conventional analysis, a naive bayes classifier is used to verify the validity of features which is extracted by wavelet packet analysis. The results show that the combined features of sound pressure and vibration signals can effectively indicate the degree of tool wear.