Wavelet coefficient extraction algorithm for extracting fatigue features in variable amplitude fatigue loading

Research output: Contribution to journalArticle

13 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)277-283
Number of pages7
JournalJournal of Applied Sciences
Volume10
Issue number4
DOIs
Publication statusPublished - 2010

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Fatigue of materials
Fatigue damage

Keywords

  • Extraction algorithm
  • Fatifue strain signal
  • Mission signal
  • Morlet wavelet coefficient

ASJC Scopus subject areas

  • General

Cite this

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title = "Wavelet coefficient extraction algorithm for extracting fatigue features in variable amplitude fatigue loading",
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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AU - Putra, T. E.

AU - Abdullah, Shahrum

AU - Nuawi, Mohd. Zaki

AU - Mohd Nopiah, Zulkifli

PY - 2010

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N2 - 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.

AB - 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.

KW - Extraction algorithm

KW - Fatifue strain signal

KW - Mission signal

KW - Morlet wavelet coefficient

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