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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
