Improved empirical wavelet denoising algorithm with application to whirling detection in deep hole drilling process

Abstract

This paper investigates the empirical wavelet denoising algorithm, to extract the high multiple frequency signals of rotation frequency from the spindle vibration signal in deep hole drilling. With the characteristic of adaptive frequency partition, empirical wavelet transform is introduced to decompose the vibration signal. Considering the influence of background noise on the vibration signal, an improved threshold denoising method is proposed to remove the noise of the spindle vibration signal. Thus, an improved empirical wavelet denoising algorithm is proposed for the high multiple frequency signals of rotation frequency extraction. The improved empirical wavelet denoising algorithm is combined with energy entropy to detect whirling in deep hole drilling process.