DocumentCode
3388507
Title
Sigma-Sampling Wavelet Denoising for Structural Health Monitoring
Author
Medda, Alessio ; Chicken, Eric ; DeBrunner, Victor
Author_Institution
Department of Electrical and Computer Engineering, FAMU-FSU College of Engineering, Florida State University
fYear
2007
fDate
26-29 Aug. 2007
Firstpage
119
Lastpage
122
Abstract
Structural Health Monitoring (SHM) techniques are non-destructive evaluation methods that try to detect, locate and assess the structural damage of a structure. The presence of damage in a structure often results in very small changes in the vibration response of the structure. It is very difficult to detect these changes due to their low order of magnitude relative to the vibration signal. A wavelet method is proposed to preprocess the signal prior to damage analysis in order to improve its signal to noise ratio and bring the vibration signal damage signature to a detectable level. Because of the characteristics of the vibration signal, standard thresholding techniques do not yield useful results. Our proposed method estimates the variance from automatically selected, structure-free portions of the vibration response and then uses this value to threshold the wavelet coefficients prior to reconstruction. This novel technique has been called sigma-sampling thresholding.
Keywords
Background noise; Computerized monitoring; Discrete wavelet transforms; Educational institutions; Noise reduction; Power engineering and energy; Signal processing; Statistics; Wavelet coefficients; Wavelet packets; Array signal processing; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2007. SSP '07. IEEE/SP 14th Workshop on
Conference_Location
Madison, WI, USA
Print_ISBN
978-1-4244-1198-6
Electronic_ISBN
978-1-4244-1198-6
Type
conf
DOI
10.1109/SSP.2007.4301230
Filename
4301230
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