Master of Science in Electrical Engineering (MSEE)


Electrical and Computer Engineering

Document Type



Detection of yield zones using nondestructive testing (NDT) technology for assessing the structural integrity of the existing steel buildings/bridges is extremely important. The average energy over the “effective echoes” (in “good” signal quality) is a robust feature for the yield detection in steel structures. Nevertheless, this average-energy feature extraction requires rigorous manual data-acquisition and human operation. Therefore, in this thesis, we make the first-ever attempt to design a totally-blind and automatic steel-structure yielddetection mechanism, which requires neither the a priori information about the signal nor the human effort in calibration, operation, or data analysis. This new scheme is built upon a robust preprocessor, which involves both blind-signature-signal-extraction and zero-crossingrate thresholding, to identify the starting and terminal time points of each ultrasonic echo. Thus, the new computer-aided system can easily estimate the signal-to-noise ratios and automatically extract the effective echoes to calculate the corresponding average energy. The performance reflected by the receiver-operating characteristic (ROC) curves of the proposed method is very close to that of the conventional human-operating technique. Hence one may save much human effort in the sacrifice of very little detection accuracy by using our proposed new system.



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Committee Chair

Wu, Hsiao-Chun