An identification method for spindle rotation error of a diamond turning machine based on the wavelet transform

This paper presents an identification method for the spindle rotation error from the flatness error in the workpiece surface. The spindle rotation error is identified by the wavelet transform, Weierstrass function, and power spectral density (PSD). The flatness error comprises various errors of the machine tool, such as spindle rotation error, guideway error, motor error, and ball screw error, therefore, wavelet transform is used to process the measured result of the workpiece and the signal is decomposed into high-frequency and low-frequency signal. Weierstrass function is used to fit the spindle rotation error. According to the PSD analysis of the processed signal in the frequency domain, the spindle rotation error is identified from the measured flatness error, this method provides a basis for the identification of machine tool errors.