Signal Processing and Pattern Recognition of Ultrasonic Waveforms for the Nondestructive Evaluation of Materials.
Final technical rept., 15 May 76-14 May 77,
CLEMSON UNIV S C DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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The overall goal of this project has been to further investigate signal processing and pattern recognition techniques as to how they apply in the nondestructive evaluation of materials for classifying ultrasonic pulse echo waveforms. Computer programs were developed to implement algorithms to generate power spectrum, cepstrum, and auto-correlation waveforms from the ultrasonic pulse echo waveforms. These algorithms have a firm statistical foundation and also have properties associated with them that allow the Fast Fourier Transform to be utilized in an efficient manner. Also, statistical features were extracted from the waveforms. The features were then input to pattern recognition techniques in order to classify the data into appropriate material defects. The procedure outlined above was implemented with 49 ultrasonic pulse echo waveforms obtained from flat-bottom holes of eight different diameters. A recognition accuracy of 98 has been attained when the flat-bottom holes are classified into two categories using only one feature from the original ultrasonic pulse echo waveforms reflected from the flat-bottom holes. The same results are achieved when the one feature is either the maximum amplitude, the root-mean-square value, or the variance of the waveform. An unexpected result was also observed when a time series method was applied to the portions of the ultrasonic pulse echo waveforms that were reflected from the backwalls instead of the flat-bottom holes.
- Computer Programming and Software
- Test Facilities, Equipment and Methods