Time-Frequency Analysis for Cutting Tools Wear Characteristics

To monitor the tool wear states in drilling, a new method is proposed to obtain the signal characteristics based on the wavelet transformation. The method can reflect the tool wear states by using discrete dyadic wavelet transform. The cutting force signals of cutting process are decomposed; and the values of the decomposed signals in different scales are taken as the feature vectors. The pattern identification is used to monitor the tool wear states in real time. The method can identify the tool wear states correctly by choosing the suitable standard samples. The result shows that the proposed method is suitable for real-time implementation in manufacturing application, and has good identification precision and high efficiency