Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction

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ZHOU, Youhang ;LI, Yong ;LIU, Hanjiang .
Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 65, n.4, p. 219-229, may 2019. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/>. Date accessed: 15 dec. 2019. 
doi:http://dx.doi.org/10.5545/sv-jme.2018.5726.
Zhou, Y., Li, Y., & Liu, H.
(2019).
Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction.
Strojniški vestnik - Journal of Mechanical Engineering, 65(4), 219-229.
doi:http://dx.doi.org/10.5545/sv-jme.2018.5726
@article{sv-jmesv-jme.2018.5726,
	author = {Youhang  Zhou and Yong  Li and Hanjiang  Liu},
	title = {Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {65},
	number = {4},
	year = {2019},
	keywords = {vibration signal; feature intensification; wavelet packet decomposition; spectral subtraction},
	abstract = {To address the difficulty in extracting the features of vibration signals under intense background noise, a new method is proposed based on wavelet packet multi-band spectral subtraction to intensify vibration signal features in drilling processing. First, it is assumed that the spindle vibration signal of machine idling and the vibration signal caused when the tool cuts the workpiece are independent of each other, and the machine’s idling signal is perceived as the ‘additive noise’ of the monitoring signal in light of the spectral subtraction principles. Secondly, in line with the characteristics of vibration signals in the drilling process, the ‘additive noise’ and monitoring signal are split into multiple frequency bands via wavelet packet decomposition. Eventually, spectral subtraction is performed independently in each band, and the vibration signals are reconstructed. The simulations and experimental results indicate that the new method should effectively eliminate the impact of environmental noise on the process of feature extraction to intensify the features of the monitoring signal.},
	issn = {0039-2480},	pages = {219-229},	doi = {10.5545/sv-jme.2018.5726},
	url = {https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/}
}
Zhou, Y.,Li, Y.,Liu, H.
2019 May 65. Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 65:4
%A Zhou, Youhang 
%A Li, Yong 
%A Liu, Hanjiang 
%D 2019
%T Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction
%B 2019
%9 vibration signal; feature intensification; wavelet packet decomposition; spectral subtraction
%! Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction
%K vibration signal; feature intensification; wavelet packet decomposition; spectral subtraction
%X To address the difficulty in extracting the features of vibration signals under intense background noise, a new method is proposed based on wavelet packet multi-band spectral subtraction to intensify vibration signal features in drilling processing. First, it is assumed that the spindle vibration signal of machine idling and the vibration signal caused when the tool cuts the workpiece are independent of each other, and the machine’s idling signal is perceived as the ‘additive noise’ of the monitoring signal in light of the spectral subtraction principles. Secondly, in line with the characteristics of vibration signals in the drilling process, the ‘additive noise’ and monitoring signal are split into multiple frequency bands via wavelet packet decomposition. Eventually, spectral subtraction is performed independently in each band, and the vibration signals are reconstructed. The simulations and experimental results indicate that the new method should effectively eliminate the impact of environmental noise on the process of feature extraction to intensify the features of the monitoring signal.
%U https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/
%0 Journal Article
%R 10.5545/sv-jme.2018.5726
%& 219
%P 11
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 65
%N 4
%@ 0039-2480
%8 2019-05-06
%7 2019-05-06
Zhou, Youhang, Yong  Li, & Hanjiang  Liu.
"Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction." Strojniški vestnik - Journal of Mechanical Engineering [Online], 65.4 (2019): 219-229. Web.  15 Dec. 2019
TY  - JOUR
AU  - Zhou, Youhang 
AU  - Li, Yong 
AU  - Liu, Hanjiang 
PY  - 2019
TI  - Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2018.5726
KW  - vibration signal; feature intensification; wavelet packet decomposition; spectral subtraction
N2  - To address the difficulty in extracting the features of vibration signals under intense background noise, a new method is proposed based on wavelet packet multi-band spectral subtraction to intensify vibration signal features in drilling processing. First, it is assumed that the spindle vibration signal of machine idling and the vibration signal caused when the tool cuts the workpiece are independent of each other, and the machine’s idling signal is perceived as the ‘additive noise’ of the monitoring signal in light of the spectral subtraction principles. Secondly, in line with the characteristics of vibration signals in the drilling process, the ‘additive noise’ and monitoring signal are split into multiple frequency bands via wavelet packet decomposition. Eventually, spectral subtraction is performed independently in each band, and the vibration signals are reconstructed. The simulations and experimental results indicate that the new method should effectively eliminate the impact of environmental noise on the process of feature extraction to intensify the features of the monitoring signal.
UR  - https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/
@article{{sv-jme}{sv-jme.2018.5726},
	author = {Zhou, Y., Li, Y., Liu, H.},
	title = {Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {65},
	number = {4},
	year = {2019},
	doi = {10.5545/sv-jme.2018.5726},
	url = {https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/}
}
TY  - JOUR
AU  - Zhou, Youhang 
AU  - Li, Yong 
AU  - Liu, Hanjiang 
PY  - 2019/05/06
TI  - Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 65, No 4 (2019): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2018.5726
KW  - vibration signal, feature intensification, wavelet packet decomposition, spectral subtraction
N2  - To address the difficulty in extracting the features of vibration signals under intense background noise, a new method is proposed based on wavelet packet multi-band spectral subtraction to intensify vibration signal features in drilling processing. First, it is assumed that the spindle vibration signal of machine idling and the vibration signal caused when the tool cuts the workpiece are independent of each other, and the machine’s idling signal is perceived as the ‘additive noise’ of the monitoring signal in light of the spectral subtraction principles. Secondly, in line with the characteristics of vibration signals in the drilling process, the ‘additive noise’ and monitoring signal are split into multiple frequency bands via wavelet packet decomposition. Eventually, spectral subtraction is performed independently in each band, and the vibration signals are reconstructed. The simulations and experimental results indicate that the new method should effectively eliminate the impact of environmental noise on the process of feature extraction to intensify the features of the monitoring signal.
UR  - https://www.sv-jme.eu/article/a-new-approach-to-intensify-features-of-vibration-signals-in-drilling-processing/
Zhou, Youhang, Li, Yong, AND Liu, Hanjiang.
"Feature Enhancement Method for Drilling Vibration Signal by Using Wavelet Packet Multi-band Spectral Subtraction" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 65 Number 4 (06 May 2019)

Authors

Affiliations

  • Xiangtan University, School of Mechanical Engineering, China 1

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 65(2019)4, 219-229

https://doi.org/10.5545/sv-jme.2018.5726

To address the difficulty in extracting the features of vibration signals under intense background noise, a new method is proposed based on wavelet packet multi-band spectral subtraction to intensify vibration signal features in drilling processing. First, it is assumed that the spindle vibration signal of machine idling and the vibration signal caused when the tool cuts the workpiece are independent of each other, and the machine’s idling signal is perceived as the ‘additive noise’ of the monitoring signal in light of the spectral subtraction principles. Secondly, in line with the characteristics of vibration signals in the drilling process, the ‘additive noise’ and monitoring signal are split into multiple frequency bands via wavelet packet decomposition. Eventually, spectral subtraction is performed independently in each band, and the vibration signals are reconstructed. The simulations and experimental results indicate that the new method should effectively eliminate the impact of environmental noise on the process of feature extraction to intensify the features of the monitoring signal.

vibration signal; feature intensification; wavelet packet decomposition; spectral subtraction