Sparsity enhancement for blind deconvolution of ultrasonic signals in nondestructive testing application

The received signal in ultrasonic pulse-echo inspection can be modeled as a convolution between an impulse response and the reflection sequence, which is the impulse characteristic of the inspected object. Deconvolution aims at approximately inverting this process to improve the time resolution so that the overlap between echoes from closely spaced reflectors becomes small. This paper presents a modified minimum entropy blind deconvolution algorithm for deconvolving ultrasonic signals. Enhancement of the resolution is achieved by using the presented method. In addition, the presented approach will, in many cases, lead to a faster computation. A nonlinear function is the key point to the efficiency of the modified blind deconvolution algorithm, which is used to increase the sparsity of the iteration output and to decrease the influence of the added noise by replacing each iteration output by output of the nonlinear function. Simulations showed the efficiency of the modification as compared with minimum entropy deconvolution when deconvolving synthetic ultrasonic signals. Experimental results using real ultrasonic data evaluated further that the exact solution consistently yields good performance. The thickness of a thin steel sample can be calculated by the modified blind deconvolution filter with a reasonable accuracy.