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Proceedings Paper

Pipeline flaw detection with wavelet packets and GAs
Author(s): Stephen W. Kercel; Raymond W. Tucker; Venugopal K. Varma
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Paper Abstract

This paper is concerned with the detection of physical flaws on pipe walls in gas pipelines. The sensor technology is EMAT, a non-contact ultrasonic technology. One EMAT is used as a transmitter, exciting an ultrasonic impulse into the pipe wall. Another EMAT located a few inches away from the first is used as a receiving transducer. This paper reports on the identification of flaw signatures in the receiver output. The first step in flaw characterization is to perform wavelet analysis of the signature. Being non-shift-invariant, an array of coefficients of a discrete wavelet transfor of a signal is not directly suitable as a pattern recognition feature. However, comparing composite properties of the signal on different scales is useful, because the more conversion caused by a flaw, changes the composite properties of the signal in wavelet space. For EMAT data, the useful information projects onto five mutually orthogonal wavelet scales. This paper reports onteh use of a robust 17-dimensional feature vector that mutually orthogonal wavelet scales. This paper reports on the use of a robust 17-dimensional featuer vector that consistently distinguishes "flaw" signatures from "no-flaw" signatures in a substantial collection of experimental data.

Paper Details

Date Published: 4 August 2003
PDF: 10 pages
Proc. SPIE 5103, Intelligent Computing: Theory and Applications, (4 August 2003); doi: 10.1117/12.496975
Show Author Affiliations
Stephen W. Kercel, Oak Ridge National Lab. (United States)
Raymond W. Tucker, Oak Ridge National Lab. (United States)
Venugopal K. Varma, Oak Ridge National Lab. (United States)


Published in SPIE Proceedings Vol. 5103:
Intelligent Computing: Theory and Applications
Kevin L. Priddy; Peter J. Angeline, Editor(s)

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