In order to eliminate the hole diameter error caused by tool wear in robot automatic drilling system

a method based on spindle current discrete wavelet transform for tool wear state online monitoring and life prediction was proposed. Firstly

according to the fluctuation law of the spindle current signal and the requirements of the regularization

similarity and smoothness of the curve error of the wavelet signal

the 3rd-order Daubechies wavelet base is selected to carry out the discrete decomposition of the spindle current signal. Combined with the law of tool wear

the 3rd-order lowfrequency decomposition of the current signal is selected as the most effective feature of tool wear state monitoring. The first order high frequency decomposition of the current signal is carried out by discrete Fourier transform to obtain the frequency characteristics of the high frequency component

which provides a basis for electromagnetic compatibility design. Finally

the least square method was used to fit the linear relationship between tool wear and spindle current characteristic value

and realized the online monitoring of spindle tool wear state and the prediction of tool life by monitoring the characteristic value of spindle current.