An approach based on wavelet packet decomposition and HilbertHuang transform (WPDHHT) for spindle bearings condition monitoring

Law, Leh Sung and Kim, Jong Hyun and Liew , Willey Yun Hsien and Lee, Sun Kyu (2012) An approach based on wavelet packet decomposition and HilbertHuang transform (WPDHHT) for spindle bearings condition monitoring. Mechanical Systems and Signal Processing, 33 . pp. 197-211. ISSN 0888-3270

[img]
Preview
PDF
44Kb

Official URL: http://dx.doi.org/10.1016/j.ymssp.2012.06.004

Abstract

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 HilbertHuang 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 WPDHHT 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.

Item Type:Article
Uncontrolled Keywords:Acoustic emission, Bearings, Condition monitoring, HilbertHuang transform, Spindle, Wavelet packet decomposition, Acceleration data, Acoustic emission signal, Good correlations, Hilbert, Hilbert Huang transforms, Monitoring techniques, Nonlinear and non-stationary signals, Pre loads, Radial error motion, Running conditions, Spindle, Spindle bearing, Spindle systems, Temperature increase, Wavelet Packet Decomposition, Acoustic emission testing, Acoustic emissions, Bearings (structural), Condition monitoring, Wavelet analysis, Mathematical transformations
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:5284
Deposited By:IR Admin
Deposited On:30 Oct 2012 15:58
Last Modified:18 Feb 2015 10:05

Repository Staff Only: item control page


Browse Repository
Collection
   Articles
   Book
   Speeches
   Thesis
   UMS News
Search
Quick Search

   Latest Repository

Link to other Malaysia University Institutional Repository

Malaysia University Institutional Repository