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Journal of Applied Sciences
  Year: 2010 | Volume: 10 | Issue: 4 | Page No.: 277-283
DOI: 10.3923/jas.2010.277.283
 
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Wavelet Coefficient Extraction Algorithm for Extracting Fatigue Features in Variable Amplitude Fatigue Loading

T.E. Putra, S. Abdullah, M.Z. Nuawi and Z.M. Nopiah

Abstract:
An extraction computational algorithm for fatigue feature editing is presented in this study. The magnitude of the time domain Morlet wavelet coefficient level was used as the parameter to set gate value for the eliminating process of the 60 sec original signal. It was important to maintain the signal statistical parameters and the total fatigue damage of the mission signal as close as to the original signal, with the retention of the original load sequences. At the end of the process, by using this approach, segments containing the higher Morlet wavelet coefficients that contribute to the more fatigue damaging events were retained and were then joined so produce the optimum mission signal length of 13.8 sec. This short signal gave a 77% reduction in length with only 8.7% reduction in the fatigue damage. In conclusion, the extraction of the fatigue features using the Morlet wavelet successfully created a new mission signal which retains the majority of the higher fatigue damaging events in the time history.
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How to cite this article:

T.E. Putra, S. Abdullah, M.Z. Nuawi and Z.M. Nopiah, 2010. Wavelet Coefficient Extraction Algorithm for Extracting Fatigue Features in Variable Amplitude Fatigue Loading. Journal of Applied Sciences, 10: 277-283.

DOI: 10.3923/jas.2010.277.283

URL: https://scialert.net/abstract/?doi=jas.2010.277.283

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