An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring

In order to prevent possible damages to the spindle systems, reliable monitoring techniques are required to provide valuable information on the condition of the spindle condition. A technique is proposed for monitoring spindle bearings conditions via the use of acoustic emission (AE) signals, which...

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Main Authors: Liew, Willey Yun Hsien, Law, Leh-Sung, Kim, Jong Hyun, Lee, Sun-Kyu
Format: Article
Language:English
Published: Elsevier 2012
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Online Access:https://eprints.ums.edu.my/id/eprint/14932/1/An_approach_based_on_wavelet_packet_decomposition_and_Hilbert.pdf
https://eprints.ums.edu.my/id/eprint/14932/
http://dx.doi.org/10.1016/j.ymssp.2012.06.004
https://doi.org/10.1016/j.ymssp.2012.06.004
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Institution: Universiti Malaysia Sabah
Language: English
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spelling my.ums.eprints.149322024-03-11T02:33:41Z https://eprints.ums.edu.my/id/eprint/14932/ An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring Liew, Willey Yun Hsien Law, Leh-Sung Kim, Jong Hyun Lee, Sun-Kyu TJ Mechanical engineering and machinery In order to prevent possible damages to the spindle systems, reliable monitoring techniques are required to provide valuable information on the condition of the spindle condition. A technique is proposed for monitoring spindle bearings conditions via the use of acoustic emission (AE) signals, which implements Hilbert–Huang transform (HHT) analysis to extract the crucial characteristic from the measured data to correlate spindle running condition. The HHT becomes a promising technique in extracting the properties of nonlinear and non-stationary signal. However, the original HHT has several deficiencies, which eventually lead to misinterpretation to the final results. The improved version of HHT is proposed and used to overcome the weakness of the original HHT. The simulation and experimental results are used to verify the effectiveness of the WPD–HHT and therefore Hilbert marginal spectral, compared to traditional Fourier transform. Experimental results are presented to examine and explore the effectiveness of AE for monitoring spindle bearings conditions. It is concluded that good correlation existed between the results obtained by AE data and the increase in the preload, and change in the dimensions and geometry of the spindle bearings and their housings as the temperature increases. In support of this finding, vibration and acceleration data are also used to assess the amount changes in the antistrophic stiffness and radial error motion. Elsevier 2012-11 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/14932/1/An_approach_based_on_wavelet_packet_decomposition_and_Hilbert.pdf Liew, Willey Yun Hsien and Law, Leh-Sung and Kim, Jong Hyun and Lee, Sun-Kyu (2012) An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring. Mechanical Systems and Signal Processing, 33. pp. 197-211. ISSN 0888-3270 http://dx.doi.org/10.1016/j.ymssp.2012.06.004 https://doi.org/10.1016/j.ymssp.2012.06.004
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Liew, Willey Yun Hsien
Law, Leh-Sung
Kim, Jong Hyun
Lee, Sun-Kyu
An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
description In order to prevent possible damages to the spindle systems, reliable monitoring techniques are required to provide valuable information on the condition of the spindle condition. A technique is proposed for monitoring spindle bearings conditions via the use of acoustic emission (AE) signals, which implements Hilbert–Huang transform (HHT) analysis to extract the crucial characteristic from the measured data to correlate spindle running condition. The HHT becomes a promising technique in extracting the properties of nonlinear and non-stationary signal. However, the original HHT has several deficiencies, which eventually lead to misinterpretation to the final results. The improved version of HHT is proposed and used to overcome the weakness of the original HHT. The simulation and experimental results are used to verify the effectiveness of the WPD–HHT and therefore Hilbert marginal spectral, compared to traditional Fourier transform. Experimental results are presented to examine and explore the effectiveness of AE for monitoring spindle bearings conditions. It is concluded that good correlation existed between the results obtained by AE data and the increase in the preload, and change in the dimensions and geometry of the spindle bearings and their housings as the temperature increases. In support of this finding, vibration and acceleration data are also used to assess the amount changes in the antistrophic stiffness and radial error motion.
format Article
author Liew, Willey Yun Hsien
Law, Leh-Sung
Kim, Jong Hyun
Lee, Sun-Kyu
author_facet Liew, Willey Yun Hsien
Law, Leh-Sung
Kim, Jong Hyun
Lee, Sun-Kyu
author_sort Liew, Willey Yun Hsien
title An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
title_short An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
title_full An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
title_fullStr An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
title_full_unstemmed An approach based on wavelet packet decomposition and Hilbert-Huang transform (WPD-HHT) for spindle bearings condition monitoring
title_sort approach based on wavelet packet decomposition and hilbert-huang transform (wpd-hht) for spindle bearings condition monitoring
publisher Elsevier
publishDate 2012
url https://eprints.ums.edu.my/id/eprint/14932/1/An_approach_based_on_wavelet_packet_decomposition_and_Hilbert.pdf
https://eprints.ums.edu.my/id/eprint/14932/
http://dx.doi.org/10.1016/j.ymssp.2012.06.004
https://doi.org/10.1016/j.ymssp.2012.06.004
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