| Structural health monitoring (SHM) is a major concern in engineering community. SHM sets out to determine the health of a structure by reading an array of sensors that are embedded (permanently attached) into the structure and monitored over time. It assets the state of structural health through appropriate data processing and interpretation, and may predict the remaining life of the structure in the long run. Most state of the art SHM techniques include E/M impedance and Lamb wave propagation approaches using piezoelectric wafer active sensors (PWAS). However, these methods require bulky, expensive instrumentation equipments, and intensive human involvement for data processing and interpretation to identify structure defects. This makes it impossible to reach long-term SHM goal and achieve in-situ and online SHM.;This dissertation is focus on instrumentation, signal processing and interpretation for SHM using PWAS.;In part I, instrumentation of impedance was extensively studied. A number of impedance measurement techniques, such as sine-correlation, cross-correlation, Fourier transform methods using stepped-sine excitations, transfer function method using synthesized broadband excitations, were explored theoretically and experimentally. Compact and low-cost impedance analyzer prototypes based on data acquisition (DAQ) devices and stand-alone digital signal processor (DSP) board were developed to replace conventional laboratory HP4194 impedance analyzer, which is always the designated instrument for E/M impedance SHM approach. Discussion on the dual use of the compact impedance hardware platform for Lamb wave propagation SHM approaches was also presented.;In part II, the dispersion issue of Lamb wave was first explored. Lamb wave dispersion compensation algorithms were studied, compared and applied to a 1D linear PWAS phased array to improve the array's resolution for damage detection. Next, theoretical basis of Lamb wave time-reversal, as a baseline-free damage detection SHM technique, was developed. The PWAS Lamb wave mode tuning effect on the time reversal procedure was studied. In addition, an adaptive signal decomposition method, i.e., matching pursuit decomposition (MPD) based on Gabor and chirplet dictionaries, was explored to automatically extract Lamb wave packet parameters, such as center frequency, time of flight (TOF). Theory of Lamb wave mode identification using chirplet MPD was developed. It correlates low-frequency Lamb wave modes (e.g., S0 and A0) with the sign of chirp rate.;Part III presents several applications to demonstrate and verify the theoretical work developed in Part I and II, including: (1) a spacecraft panel disbond detection using the newly developed impedance analyzer; (2) PWAS phased array resolution improvement using the dispersion compensation algorithm; (3) Lamb wave TOF estimation using MPD and dispersion compensation methods; (4) sparse array resolution improvement using the MPD method.;Part IV presents some novel applications with PWAS, including the utilization of PWAS as a smart sensor for crack growth monitoring under fatigue load, development of bio-PWAS resonator for monitoring capsule formation after implant, and development of high-temperature PWAS (HT-PWAS) for extreme environments. |
