Abstract:
This study explores an application of the wavelet denoising technique
in a fatigue road load variable amplitude data set. In this study, the
wavelet denoising application has been implemented using the 4th order
of Daubechies family, with the adaptation of fifteen levels decomposition
process. From the view of current research trend, the wavelet-based denoising
approach is widely used using vibration random signal, but it is rarely
been used in the scope of fatigue road loadings, or also known as fatigue
strain signals. The idea of this study came from the some previous vibration
analysis research and it was found to be suited to the approach of fatigue
signal denoising process. High amplitude events in a fatigue road signal
are very important and they should be retained because of these features
caused significant damage of the components, particularly in automotive
applications. After the fatigue signal has been denoised, the global signal
statistical calculation and fatigue damage/life analysis were performed
in order to validate the applicability of this denoising technique. From
the analysis, it was found that the wavelet denoising approach was not
suitable to analyse fatigue data and the major concern is the omission
of high amplitude events from the original road loading, hence to a significant
fatigue damage difference when compared to the edited road loading.
S. Abdullah, S.N. Sahadan, M.Z. Nuawi and Z.M. Nopiah, 2008. Fatigue Road Signal Denoising Process Using the 4th Order of Daubechies Wavelet Transforms
. Journal of Applied Sciences, 8: 2496-2509.
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