On the Processing of Highly Nonlinear Solitarywaves andudGuided Ultrasonic Waves for Structural Health Monitoringudand Nondestructive Evaluation

摘要

The in-situ measurement of thermal stress in civil and mechanical structures may preventudstructural anomalies such as unexpected buckling. In the first half of the dissertation, we presentuda study where highly nonlinear solitary waves (HNSWs) were utilized to measure axial stress inudslender beams. HNSWs are compact non-dispersive waves that can form and travel in nonlinearudsystems such as one-dimensional chains of particles. The effect of the axial stress acting in audbeam on the propagation of HNSWs was studied. We found that certain features of the solitaryudwaves enable the measurement of the stress.ududIn general, most guided ultrasonic waves (GUWs)-based health monitoring approachesudfor structural waveguides are based on the comparison of testing data to baseline data. In theudsecond half of the dissertation, we present a study where some baseline-free signal processingudalgorithms were presented and applied to numerical and experimental data for the structuraludhealth monitoring (SHM) of underwater or dry structures. The algorithms are based on one orudmore of the following: continuous wavelet transform, empirical mode decomposition, Hilbertudtransform, competitive optimization algorithm, probabilistic methods. Moreover, experimentaluddata were also processed to extract some features from the time, frequency, and joint timefrequencyuddomains. These features were then fed to a supervised learning algorithm based onudartificial neural networks to classify the types of defect. The methods were validated using theudnumerical model of a plate and a pipe, and the experimental study of a plate in water. Inudexperiment, the propagation of ultrasonic waves was induced by means of laser pulses orudtransducer and detected with an array of immersion transducers. The results demonstrated thatudthe algorithms are effective, robust against noise, and able to localize and classify the damage.