Automatic flaw detection for tube support plate signals

Cho, Yongju; Basart, John P.
May 2000
AIP Conference Proceedings;2000, Vol. 509 Issue 1, p839
Academic Journal
An automatic flaw detection algorithm for signals in tube support plate (TSP) region was created using the Affine for preprocessing, Wavelet transformation for feature extraction, and regression for evaluation. Tube support plate data were extracted from an entire tube data set. The Affine transformation is used to suppress TSP signals since they are not of interest. However, it does not suppress the TSP signal perfectly but leaves residuals. The residual signal is then transformed using Wavelets for feature extraction. The Wavelet transformation with the residual data provides time and frequency information that are the important factors in determining patterns of flaw and noise signals. The possible defective signals extracted from the Wavelet transformation are evaluated using phase angle information. A line is fit by least square to the lissajous pattern of the residuals. If the phase of the line lies in the approximate from 40 to 140 degrees, the candidate flaw is claimed to be a real flaw. © 2000 American Institute of Physics.


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