Tool Condition Monitoring Using Wavelet Analysis with Savitzky-Golay Filter

Abstract

According to the application characteristics of wavelet transform to time series, the wavelet coefficients of time series of force in the process of tool use are extracted by wavelet transform as features, fused with support vector regression and back propagation neural network, and applied to tool condition monitoring. Savitzky-Golay convolution smoothing algorithm is added to obtain better experimental results.