UC San Diego

Civil structures undergo progressive deterioration due to ageing under the effects of environmental conditions. This deterioration has become a worldwide concern. In addition, natural and man-made hazards such as earthquakes, hurricanes, and explosions can also cause structural damages or exacerbate existing damage. Vibration-based structural damage identification and health monitoring has been the subject of significant research in structural engineering over the past decade. The research work presented in this dissertation consists of: (1) a comparative study of output-only system identification techniques as applied to the Alfred Zampa Memorial Bridge based on dynamic field test data, through which the performance of different output-only system identification methods applied to the bridge vibration data and corresponding to different excitation sources is investigated; (2) development of a simulation framework for wind-induced ambient vibration response of Vincent Thomas Bridge using a detailed three-dimensional finite element model of the bridge and a state-of-the-art stochastic wind excitation model, which provides a validated framework to study the effects of realistic damage scenarios in long-span cable-supported bridges on their identified modal parameters; (3) damage identification of a full-scale seven-story reinforced concrete building slice tested on the UCSD-NEES shake table using a sensitivity-based finite element model updating strategy based on the modal parameters identified from ambient vibration data; (4) development and implementation of a state-of-the-art long-term continuous monitoring system on the Voigt Bridge Testbed, which will serve as a live laboratory for structural health monitoring technologies; (5) development of an automated system identification procedure for extracting modal parameters of the Voigt Bridge as a function of time; and (6) investigation of the environmental effects on the identified modal parameters of the Voigt Bridge and objective criterion for damage detection under varying environmental conditions. The research work presented and the results obtained in this dissertation contribute significantly to the development of robust and reliable vibration-based structural health monitoring systems for large and complex real-world structures