Paper
1 May 2003 Characterization of gas pipeline flaws using wavelet analysis
Raymond W. Tucker Jr., Stephen W. Kercel, Venugopal K. Varma
Author Affiliations +
Proceedings Volume 5132, Sixth International Conference on Quality Control by Artificial Vision; (2003) https://doi.org/10.1117/12.515157
Event: Quality Control by Artificial Vision, 2003, Gatlinburg, TE, United States
Abstract
As U.S. natural gas supply pipelines are aging, non-destructive inspection techniques are needed to maintain the integrity and reliability of the natural gas supply infrastructure. Ultrasonic waves are one promising method for non-destructive inspection of pipeline integrity. As the waves travel through the pipe wall, they are affected by the features they encounter. In order to build a practical inspection system that uses ultrasonic waves, an analysis method is needed that can distinguish between normal pipe wall features, such as welds, and potentially serious flaws, such as cracks and corrosion. Ideally, the determination between “flaw” and “no-flaw” must be made in real-time as the inspection system passes through the pipe. Because wavelet basis functions share some common traits with ultrasonic waves, wavelet analysis is particularly well-suited for this application. Using relatively simple features derived from the wavelet analysis of ultrasonic wave signatures traveling in a pipe wall, we have successfully demonstrated the ability to distinguish between the “flaw” and “no-flaw” classes of ultrasonic features.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raymond W. Tucker Jr., Stephen W. Kercel, and Venugopal K. Varma "Characterization of gas pipeline flaws using wavelet analysis", Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); https://doi.org/10.1117/12.515157
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CITATIONS
Cited by 14 scholarly publications and 1 patent.
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KEYWORDS
Wavelets

Ultrasonics

Inspection

Corrosion

Waveguides

Safety

Signal analysis

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