Defect deconvolution using 3rd order statistics for Ultrasonic Nondestructive Testing
Author | Qidwai, Uvais |
Author | Bettayeb, Maamar |
Author | Yamani, Ahmed |
Available date | 2009-12-29T10:44:51Z |
Publication Date | 2007-02-12 |
Publication Name | 9th International Symposium on Signal Processing and Its Applications (ISSPA) 2007 |
Citation | Qidwai, U.; Bettayeb, M.; Yamani, A., "Defect deconvolution using 3rd order statistics for Ultrasonic Nondestructive Testing," Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on , vol., no., pp.1,4, 12-15 Feb. 2007 |
Abstract | Ultrasonic nondestructive testing (NDT) is primarily based upon the detection and classification of a defect in the field of industrial materials. This information is useful in making administrative decisions in terms of maintenance and replacement. The technique presented in this paper utilizes the concept of defect induction as a convolution process between the clean sample and the defect signature. Hence, to identify the type of defect a deconvolution approach can be useful. Due to several similarities between the ultrasonic echoes and the usual modulated sinusoids, a motivation is present to use 2nd and higher order statistics for completely defining the waveform. Such a definition, when compared with standard defects, will provide useful insight in terms of defect classifications and understanding. |
Language | en |
Publisher | IEEE |
Subject | Ultrasonic Nondestructive deconvolution flaw detection higher order statistics signal classification ultrasonic materials testing |
Type | Conference Paper |
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Computer Science & Engineering [2284 items ]