Strain Signal Characterisation Using the 4th Order of Daubechies Wavelet Transform for Fatigue Life Determination
Keywords:Decomposition, Discrete Wavelet Transform, Fatigue Analysis, Time-frequency Domain
AbstractThis paper presents the significance of Discrete Wavelet Transform to provide more accuracy by using the Wavelet (Db4) Daubechies approach to analyse original signals obtained from the actual responses of an automotive suspension system. The time-frequency domain considers both time and frequency parameters, making this approach more efficient compared to the time domain and frequency domain approaches. An original signal was obtained from three road types:Â highway road, rural road and residential road. These signals were classified into 12 levels of decomposition where each level contained its own frequency range. The decomposed signals were then analysed using fatigue analysis to obtain the fatigue damage at each interval, which was then compared to the original signal. Results show that the decomposition signals from levels 1 to level 2 for highway and residential roads and level 1 to level 3 for rural roads gave a significant value of fatigue life located in the range of 2:1 and 1:2 in the fatigue life prediction graph. In summary, the Daubechies (Db4) Wavelet approach is capable of correlating the fatigue life of those components that contribute to the failure of a suspension system.
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