This paper presents the application of a signal correlation technique to automatically classify ultrasonic A-scan signals for
defect and non-defect regions in isotropic and anisotropic materials. First, a reference A-scan signal of a non-defect area was
generated by autocorrelation and statistics. Next, the similarity between the reference signal and the signal of interest was
analyzed based on their cross-correlation. The analyzed result was quantified using the correlation coefficient and the distance
between the front and back echoes. After that, the defect mapping was defined based on these two criteria to locate the defect
area on a 2D image. This method uses statistics rather than the prior knowledge of an inspector to generate a C-scan map, and
has particular value in automated ultrasonic signal classification and characterization.
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