Miguel A. Rodríguez

Shift Invariant Wavelet Denoising of Ultrasonic Traces

Basic wavelet denoising techniques rely on a thresholding of the discrete wavelet transform (DWT) coefficients of the noisy signal. Some improvements in noise reduction efficiency can be obtained by the use of shift-invariant undecimated wavelet transforms (UWT). Ultrasonic grain noise is one of the most usual types of noise present in ultrasonic non-destructive evaluation. It comes from reflections in the material structure, and occupies a frequency band very similar to that of the echosignals of interest. In this work, new advances in the application of redundant wavelet transforms to ultrasonic grain noise reduction are presented. Wavelet denoising is applied to several sets of synthetic ultrasonic traces, which are obtained from a model that includes frequency dependent attenuation for both grain and flaw backscattered echoes, frequency dependent scattering from the grains, and an accurate model for the pulse-echo frequency response of the piezoelectric ultrasonic transducer. Two processors based on traditional DWT and alternative a trous UWT denosing have been implemented and compared, using level dependent thresholds (appropriate for correlated noise), soft thresholding, and Universal, SURE and Minimax threshold selection rules. The performances of the two processors are analyzed in terms of the mean value and standard deviation of the signal-to-noise ratio (SNR) of different sets of ultrasonic traces before and after denoising. It is shown that a trous UWT processing provides better results than DWT with a general tendency to higher quality of the resulting traces and greater robustness of the processing. It is also shown that the better performance of the UWT is mainly related to the redundancy of the representation, since there are not significant variations between the threshold values obtained with each processor.

Signal processing for ultrasonic non-destructive evaluation: two applications

The quality control in industrial plants using ultrasonic non-destructive methods is an emerging field for signal processing applications. In this paper we present a general purpose prototype for non-destructive evaluation of materials by means of ultrasonics. The basic prototype could be used in different applications, changing only the signal processing software. In this paper we will show the flexibility of our equipment by means of two different applications: the detection of microcracks in wet ceramic (tiles) and the evaluation of the moisture in cheeses. We describe the necessary signal processing for each application and the results obtained.

Denoising Ultrasound RF Signals by Wavelet Cycle Spinning Shrinkage

A speckle reduction procedure, based on wavelet Cycle Spinning (CS) Shrinkage, has been applied to radio-frequency RF pulse-echo signals. Several sets of 100 synthetic ultrasonic signals were generated using a model of speckle formation which includes frequency dependent attenuation, frequency dependent scattering, and an accurate model for the pulse-echo response of the broad band ultrasonic transducer. The frequency spectra overlapping of ultrasound signal and speckle noise is shown. The mean and standard deviation of the signal to noise ratio (SNR) of sets of 100 RF signals have been taken as denoising performance indexes. Results of CS denoising have been compared with those of Discrete Wavelet Transform (DWT) denoising, using Universal and SURE decomposition level dependent threshold selection rules. CS overcomes the lack of translation invariance of DWT providing on average a better denoising performance. A preliminary evaluation of the influence of different mother wavelets is also presented.

Wavelet cycle-spinning denoising of ultrasonic traces acquired from austenitic steel

Ultrasonic non-destructive evaluation of austenitic steel components or welded unions usually presents difficulty for small flaw detection, due to complex structure and wave scattering at grain boundaries. Ultrasonic signals from small flaws are masked by grain or structural noise whose frequency band partially overlaps the frequency response of the ultrasonic transducer. The main objective of this work is the application and performance analysis of a cycle-spinning undecimated wavelet transform processor for denoising ultrasonic traces acquired from a test block made of austenitic steel.