An Application of Wavelet Signal Processing to Ultrasonic Nondestructive Evaluation

In this paper we present a flaw signature estimation approach which utilizes the Wiener filter [1–5] along with a wavelet based procedure [6–15] to achieve both deconvolution and reduction of acoustic noise. In related ealier work by Patterson et al. [6], the wavelet transform was applied to certain components of the Wiener filter, and coefficient chopping was used to reduce acoustic noise. In the approach that we present here, the wavelet transform is applied individually to the real part and to the imaginary part of the scattering amplitude estimate determined by application of a sub-optimal form of the Wiener filter. This wavelet transform takes the real and imaginary parts, respectively, from the typical Fourier frequency domain to a wavelet phase space. In this new space, the acoustic noise shows significant separation from the flaw signature making selective pruning of wavelet coefficients an effective means of reducing the acoustic noise. The final estimates of the real and imaginary parts of the scattering amplitude are determing via an inverse wavelet transform.