The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON MATHEMATICS
Transactions ID Number: 89-558
Full Name: Shahrum Abdullah
Position: Associate Professor
Age: ON
Sex: Male
Address: Department of Mechanical and Materials Engineering Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor
Country: MALAYSIA
Tel: +60173309669
Tel prefix:
Fax:
E-mail address: shahrum@vlsi.eng.ukm.my
Other E-mails: shahrum1@gmail.com
Title of the Paper: the morlet wavelet analysis for fatigue feature clustering
Authors as they appear in the Paper: Shahrum Abdullah, Teuku Edisah Putra, Mohd. Zaki Nuawi, Zulkifli Mohd. Nopiah, Azli Arifin and Lenny Abdullah
Email addresses of all the authors: shahrum@vlsi.eng.ukm.my, edi_unsyiah@yahoo.co.id, zaki@vlsi.eng.ukm.my, zmn@vlsi.eng.ukm.my, azli@eng.ukm.my, lenny_abdul@yahoo.com
Number of paper pages: 10
Abstract: This paper presents clustering of fatigue features resulted from the segmentation of SAESUS time series data. The segmentation process was based on the Morlet wavelet coefficient amplitude level which produced 49 segments that each has overall fatigue damage. Observation of the fatigue damage and the wavelet coefficients was made on each segment. At the end of the process, the segments were clustered into three in order to identify any improvements in the data scattering for fatigue data clustering prospects. This algorithm produced a more reliable and suitable method of segment by segment analysis for fatigue strain signal segmentation. According to the findings, the higher Morlet wavelet coefficient presented damaging segment, otherwise, it was non-damaging segment. This indicated that the relationship between the Morlet wavelet coefficient and the fatigue damage was strong and parallel.
Keywords: Fatigue strain signal, Segmentation, Fatigue damage, Morlet wavelet coefficient, Clustering
EXTENSION of the file: .pdf
Special (Invited) Session: Using Morlet Wavelet Coefficients to Cluster Variable Amplitude Fatigue Features
Organizer of the Session: 640-247
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