Studies Into Vibration-Signature-Based Methods for System Identification, Damage Detection and Health Monitoring of Civil Infrastructures.

摘要

Civil infrastructures play a vital role in human societies. Recent catastrophic events due to the deficiency, failure or malfunction of these systems, claiming many lives and resulting in substantial economic loss, have attracted extensive attention focused on reviewing and amending the design and maintenance procedures of civil infrastructures. In addition to the possible failure of structural components, long-term forms of damage due to deterioration or fatigue may also necessitate regular monitoring of civil structures. Therefore, depending on the importance, use and risk, the structure of interest needs to be equipped with inspection, monitoring and maintenance systems. Structural Health Monitoring (SHM) is generally associated with any engineering methodology whose aim is to detect, locate and quantify the damage in the target system. Vibration-based techniques, as the most conventional SHM approaches, acquire and analyze the structural response using a variety of sensors mounted at different locations on the structure. The main goal of the study reported herein is to investigate and evaluate different vibration-signature-based methods for system identification, damage detection and health monitoring of civil structures. Various well-known techniques such as finite element model updating approach and damage detection methods based on artificial neural networks are studied and evaluated. Experimental data from two case studies, a quarter-scale two-span bridge system, tested at the University of Nevada, Reno, and a 1/20 scale 4-story building equipped with smart devices of magneto-rheological (MR) damper, are used for investigation and validation purposes. Guidelines are established for the optimum selection of the dominant control parameters involved in the application of some of the robust SHM approaches for achieving reliable SHM results under realistic conditions.