Sigma-Sampling Wavelet Denoising for Structural Health Monitoring
Alessio Medda, Eric Chicken, Victor DeBrunner · 2007 IEEE/SP 14th Workshop on Statistical Signal Processing · 2007
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.