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Blind Yield Detection In Steel Structure For Automatic Nondestructive Testing Using Ultrasonic Sensors, Hongting Zhang

LSU Master's Theses

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 …