An Analysis of Ultrasonic Flaw Scattering Amplitude as a Random Variable
The use of prior information is an important component in the ultrasonic detection, classification, and characterization of flaws. In order to take full advantage of advanced digitally based approaches to flaw detection, classification, and characterization, use of prior information will be critical. Some advanced techniques involve probabilistic approaches which start with a stochastic model for a flaw signal in which the flaw’s scattering amplitude is assumed to be an uncorrelated, Gaussian random variable with zero mean and known variance [1–4]. The goal of the work presented here was to analyze scattering amplitude as a random variable with emphasis on evaluation of these assumptions.
KeywordsLognormal Distribution Flaw Size Flaw Distribution Spherical Void Deterministic Nature
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- 1.Neal, S. P. 1988. A prior knowledge based optimal Wiener filtering approach to ultrasonic scattering amplitude estimation. Doctoral Dissertation. Iowa State University, Ames, IA.Google Scholar
- 2.Neal, S. P., and D. O. Thompson. 1988. The effects of prior flaw information on Wiener filter based ultrasonic flaw scattering amplitude estimation. p. 857–864. In D. O. Thompson and D. E. Chimenti (ed.) Review of progress in quantitative NDE. Vol. 7A. Plenum Press, New York.Google Scholar
- 3.Whalen, A. D. 1971. Detection of signals in noise. Academic Press, New York.Google Scholar
- 4.Elsley, R. K., J. M. Richardson, and R. C. Addison. 1980. Optimum measurement of broadband ultrasonic data. p. 916–921. In B. R. McAvoy (ed.) Ultrasonic symposium proceedings. Vol. 2. IEEE, New York.Google Scholar
- 5.Gubernatis, J. E., E. Domany, and J. A. Krumhansl. 1977. Formal aspects of the scattering of ultrasound by flaws in elastic materials. J. Appl. Phys. 48: 2804–2811.Google Scholar
- 8.Papoulis, A. 1965. Probability, random variables, and stochastic processes. McGraw-Hill, New York.Google Scholar
- 10.Hsu, D. K., and K. M. Uhl. 1987. A morphological study of porosity defects in graphite-epoxy composites. p. 1175–1184. In D. O. Thompson and D. E. Chimenti (ed.) Review of progress in quantitative NDE. Vol. 6B. Plenum Press, New York.Google Scholar
- 11.Brown, R. G. 1983. Introduction to random signal analysis and Kalman filtering. Wiley, New York.Google Scholar