Abstract
Adaptive noise cancellation techniques are ideally suited for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation. Since grain noise is generally uncorrelated, in contrast to the correlated flaw echoes, adaptive filtering algorithms exploit the correlation properties of signals in a C-scan image to enhance the signal-to-noise ratio of the output signal. In this paper, a multi-stage adaptive noise cancellation method is proposed for enhancing flaw detection in ultrasonic signals. The overall method is based on the use of an adaptive least mean square error filter with primary and reference signals derived from two adjacent positions of the transducers. Results of implementing the proposed algorithm on ultrasonic signals obtained from hard-α inclusions in titanium will be presented.
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