Data scattering of fatigue damaging segmentation in order to develop the fatigue damaging and Morlet wavelet coefficient relationship

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper presents scattering of fatigue time series data to develop a relationship between the fatigue damage and the Morlet wavelet coefficient. In order to achieve the purpose, the SAESUS strain signal was inputted into a segmentation algorithm based on the wavelet coefficient amplitude level which produces 49 segments that each has an overall fatigue damage. Observation of the fatigue damage and the wavelet coefficient was made on each segment. In the end of process, this algorithm produced a more reliable and suitable method of fatigue stain signal segmentation and segment by segment analysis to identify any improvements in the data scattering for fatigue data clustering prospects. Scatter plot was produced based on the relationship between segmental fatigue damage and its corresponding wavelet coefficient value. As the result, the relationship between the fatigue damage and the Morlet wavelet coefficient is strong and parallel, since the higher wavelet coefficient presents the higher fatigue damage, otherwise, it is the lower fatigue damage.

Original languageEnglish
Pages (from-to)605-610
Number of pages6
JournalInternational Review of Mechanical Engineering
Volume5
Issue number4
Publication statusPublished - 2011

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Fatigue damage
Fatigue of materials
Scattering
Time series

Keywords

  • Data scattering
  • Fatigue damage
  • Fatigue strain signal
  • Morlet wavelet coefficient
  • Segmentation

ASJC Scopus subject areas

  • Mechanical Engineering

Cite this

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title = "Data scattering of fatigue damaging segmentation in order to develop the fatigue damaging and Morlet wavelet coefficient relationship",
abstract = "This paper presents scattering of fatigue time series data to develop a relationship between the fatigue damage and the Morlet wavelet coefficient. In order to achieve the purpose, the SAESUS strain signal was inputted into a segmentation algorithm based on the wavelet coefficient amplitude level which produces 49 segments that each has an overall fatigue damage. Observation of the fatigue damage and the wavelet coefficient was made on each segment. In the end of process, this algorithm produced a more reliable and suitable method of fatigue stain signal segmentation and segment by segment analysis to identify any improvements in the data scattering for fatigue data clustering prospects. Scatter plot was produced based on the relationship between segmental fatigue damage and its corresponding wavelet coefficient value. As the result, the relationship between the fatigue damage and the Morlet wavelet coefficient is strong and parallel, since the higher wavelet coefficient presents the higher fatigue damage, otherwise, it is the lower fatigue damage.",
keywords = "Data scattering, Fatigue damage, Fatigue strain signal, Morlet wavelet coefficient, Segmentation",
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AU - Putra, T. E.

AU - Abdullah, Shahrum

AU - Nuawi, Mohd. Zaki

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N2 - This paper presents scattering of fatigue time series data to develop a relationship between the fatigue damage and the Morlet wavelet coefficient. In order to achieve the purpose, the SAESUS strain signal was inputted into a segmentation algorithm based on the wavelet coefficient amplitude level which produces 49 segments that each has an overall fatigue damage. Observation of the fatigue damage and the wavelet coefficient was made on each segment. In the end of process, this algorithm produced a more reliable and suitable method of fatigue stain signal segmentation and segment by segment analysis to identify any improvements in the data scattering for fatigue data clustering prospects. Scatter plot was produced based on the relationship between segmental fatigue damage and its corresponding wavelet coefficient value. As the result, the relationship between the fatigue damage and the Morlet wavelet coefficient is strong and parallel, since the higher wavelet coefficient presents the higher fatigue damage, otherwise, it is the lower fatigue damage.

AB - This paper presents scattering of fatigue time series data to develop a relationship between the fatigue damage and the Morlet wavelet coefficient. In order to achieve the purpose, the SAESUS strain signal was inputted into a segmentation algorithm based on the wavelet coefficient amplitude level which produces 49 segments that each has an overall fatigue damage. Observation of the fatigue damage and the wavelet coefficient was made on each segment. In the end of process, this algorithm produced a more reliable and suitable method of fatigue stain signal segmentation and segment by segment analysis to identify any improvements in the data scattering for fatigue data clustering prospects. Scatter plot was produced based on the relationship between segmental fatigue damage and its corresponding wavelet coefficient value. As the result, the relationship between the fatigue damage and the Morlet wavelet coefficient is strong and parallel, since the higher wavelet coefficient presents the higher fatigue damage, otherwise, it is the lower fatigue damage.

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KW - Fatigue strain signal

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KW - Segmentation

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