Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22889
Title: Optimal mother Wavelet selection for lamb wave analyses
Authors: Li, F
Meng, G
Kageyama, K
Su, Z 
Ye, L
Keywords: Lamb wave
Mother wavelet
Shannon entropy
Structural health monitoring
Wavelet transform
Issue Date: 2009
Publisher: Sage Publications Ltd
Source: Journal of intelligent material systems and structures, 2009, v. 20, no. 10, p. 1147-1161 How to cite?
Journal: Journal of Intelligent Material Systems and Structures 
Abstract: Structural health monitoring (SHM) system, usually consisting of a sensor network for collecting the structural response signal and data analysis algorithms for interpreting the signal, plays a significant role in fatigue life and damage accumulation prognostics. Wavelet transform (WT) has gained popularity as an efficient means of signal processing in SHM, in which an optimal mother wavelet-based WT can carry out feature extraction with high precision. This article is to provide criteria of optimal mother wavelet selection in Lamb wave analysis for SHM, motivation of which is that small error in Lamb wave analysis can result in much larger error in damage localization because of very fast propagating velocities of Lamb waves. A concept, Shannon entropy of wavelet coefficients, was established to calibrate the degree of optimization of the selected mother wavelet. As application, various mother wavelets selected using the proposed criteria were applied to Lamb wave signals acquired from CF/EP composite laminates containing delamination. With the optimum mother wavelet, the essential information of the delamination-generated Lamb waves was achieved with high precision. The results demonstrate the excellent capacity of the approach for selecting the most appropriate mother wavelets for Lamb wave analyses and therefore damage localization.
URI: http://hdl.handle.net/10397/22889
DOI: 10.1177/1045389X09102562
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

27
Last Week
0
Last month
1
Citations as of Nov 18, 2017

WEB OF SCIENCETM
Citations

16
Last Week
0
Last month
Citations as of Nov 21, 2017

Page view(s)

58
Last Week
1
Last month
Checked on Nov 19, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.