On effective spectrum-based ultrasonic deconvolution techniques for hidden flaw characterization

Abstract

From the pioneering works of Gericke [O. R. Gericke, J. Acoust. Soc. Am. 35, 364–368 (1963)] and some other researchers [L. Adler, K. V. Cook, and W. A. Simpson, ‘‘Ultrasonic frequency analysis,’’ in Research Techniques in Nondestructive Testing, edited by R. S. Sharpe (Academic, London, 1977), Vol. 3; A. F. Brown, ‘‘Ultrasonic spectroscopy,’’ in Ultrasonic Testing, edited by J. Szilard (Wiley, New York, 1982)], frequency spectra of ultrasonic returns form hidden flaws carry a rich amount of information usable for flaw characterization. With a proper modeling of these ultrasonic echoes, the effectiveness of such frequency analyses can be further enhanced by a process called deconvolution or inverse filtering. In this paper, the performances of several deconvolution algorithms when applied to ultrasonic pulse echoes from artificial flaws embedded in some aluminum blocks are investigated. The relative computational complexities of these algorithms are also analyzed and compared. Empirical results shall justify the applications of these algorithms for flaw characterization. Furthermore, on comparing the experimental results, simpler implementations and higher efficiencies should favor the use of the spectrum-based deconvolution techniques over time-domain techniques.

A noncontact method for determining surface density of nonporous materials with the limp-wall mass law

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