Signal denoising and ultrasonic flaw detection via overcomplete and sparse representations

Abstract

Sparse signal representations from overcomplete dictionaries are the most recent technique in the signal processing community. Applications of this technique extend into many fields. In this paper, this technique is utilized to cope with ultrasonic flaw detection and noise suppression problem. In particular, a noisy ultrasonic signal is decomposed into sparse representations using a sparse Bayesian learning algorithm and an overcomplete dictionary customized from a Gabor dictionary by incorporating some a priori information of the transducer used. Nonlinear postprocessing including thresholding and pruning is then applied to the decomposed coefficients to reduce the noise contribution and extract the flaw information. Because of the high compact essence of sparse representations, flaw echoes are packed into a few significant coefficients, and noise energy is likely scattered all over the dictionary atoms, generating insignificant coefficients. This property greatly increases the efficiency of the pruning and thresholding operations and is extremely useful for detecting flaw echoes embedded in background noise. The performance of the proposed approach is verified experimentally and compared with the wavelet transform signal processor. Experimental results to detect ultrasonic flaw echoes contaminated by white Gaussian additive noise or correlated noise are presented in the paper.

State-of-the-art review on Bayesian inference in structural system identification and damage assessment

“…In the field of guided wave/ultrasonic NDT signal processing for damage or defect detection, sparse signal recovery algorithms have also attracted increasing attention during the recent decade (Hong et al, 2006;Raghavan and Cesnik, 2007;Wu et al, 2017aWu et al, , 2017bWu et al, , 2018Zhang et al, 2008). The prior information exploited in the application is that the object being inspected contains a limited amount of damage or defects, and so the measured signal should be a linear combination of echoes reflected from these damage or defects.…”

Development of C-Line plot technique for the characterization of edge effects in acoustic imaging: A case study using flip chip package geometry

“…Our previous research showed that for the 230 MHz focused transducer, the approximate error (the root-mean squared error) using the Gabor model is smaller than 1.12% [5]. Therefore, the input displacement loads applied to the virtual transducer were modulated using the Gabor function in Eq.…”

“…The parameters in Eq. (2) were obtained by approximating a reference ultrasonic echo using the Gabor model as described in [5]. details can be found in [6,7].…”

Finite element modelling for the investigation of edge effect in acoustic micro imaging of microelectronic packages

“…In order to examine the efficiency of the Gabor model for approximating ultrasonic pulses in our system, ultrasonic echoes reflected from the front surface of a steel block in a water tank were collected using the 230 MHz focused transducer in our previous study [18]. The measured echoes were then fitted by the cosine Gabor model.…”