DocumentCode
2565686
Title
An extraction computational algorithm based on the Morlet wavelet coefficient spectrum
Author
Putra, T.E. ; Abdullah, S. ; Nuawi, M.Z.
Author_Institution
Dept. of Mech. & Mater. Eng., Univ. Kebangsaan Malaysia, Bangi, Malaysia
fYear
2009
fDate
18-19 Nov. 2009
Firstpage
68
Lastpage
73
Abstract
This paper discussed on the effectiveness of the Morlet wavelet to generate new edited signal. The 122.4 second SAESUS strain signal was edited based on the Morlet wavelet coefficient amplitude level. Segments with wavelet coefficient amplitude level lower than Cut Off Level (COL) were removed. Furthermore, extracted fatigue damaged segments were retained and then were joined in order to gain new edited signal. The signal statistical parameter and fatigue damaging values should be as accurate as possible for all signals. From the analysis, the 25,000 με was selected to be the optimum COL value since the level did not change the signal behaviour. This value gave a 14 % reduction in length with only 6.1 % reduction in the fatigue damage. This indicated that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well.
Keywords
fatigue; fatigue testing; signal processing; statistical analysis; wavelet transforms; Morlet wavelet coefficient spectrum; SAESUS strain signal; cut off level; edited signal; extraction computational algorithm; fatigue damaged segments; fatigue damaging values; signal statistical parameter; Capacitive sensors; Continuous wavelet transforms; Fatigue; Life estimation; Signal analysis; Signal processing; Testing; Time frequency analysis; Wavelet analysis; Wavelet coefficients;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-5560-7
Type
conf
DOI
10.1109/ICSIPA.2009.5478722
Filename
5478722
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