System and Damage Identification of Civil Structures

Abstract

In recent years, structural health monitoring has received increasing attention in the civil engineering research community with the objective to identify structural damage at the earliest possible stage and evaluate the remaining useful life (damage prognosis) of structures. Vibration- based, non-destructive damage identification is based on changes in dynamic characteristics (e.g., modal parameters) of a structure for identifying structural damage. Experimental modal analysis (EMA) has been used as a technology for identifying modal parameters of a structure based on its measured vibration data. It should be emphasized that the success of damage identification based on EMA depends strongly on the accuracy and completeness of the identified structural dynamic properties. The objective of the research work presented in this thesis is to develop new, and improve/extend existing system identification and damage identification methods for vibration based structural health monitoring. In the first part of the thesis, a new system identification method is developed to identify modal parameters of linear dynamic systems subjected to measured (known) arbitrary dynamic loading from known initial conditions. In addition, a comparative study is performed to investigate the performance of several state-of-the-art input-output and output-only system identification methods when applied to actual large structural components and systems. In the second part of the thesis, a finite element model updating strategy, a sophisticated damage identification method, is formulated and computer implemented. This method is then successfully applied for damage identification of two large test structures, namely a full-scale sub-component composite beam and a full-scale seven-story R/C building slice, at various damage levels. The final part of the thesis investigates, based on numerical response simulation of the seven-story building slice, the effects of the variability/uncertainty of several input factors on the variability/uncertainty of system identification and damage identification results. The results of this investigation demonstrate that the level of confidence in the damage identification results obtained through FE model updating is a function of not only the level of uncertainty in the identified modal parameters, but also choices made in the design of experiments (e.g., spatial density of measurements) and modeling errors (e.g., mesh size)