Decomposition Approach for Damage Detection, Localization, and Quantification for a 52-Story Building in Downtown Los Angeles

Abstract

Among the most challenging problems in the field of damage detection and condition assessment in large structures is the ability to reliably detect, locate, and quantify relatively small changes in their dynamic response, based on vibration signal analysis. In this study, a substructuring approach, which uses a nonparametric identification method, was applied to simulated damage data from a high-fidelity and validated three-dimensional (3D) finite element model of a 52-story high-rise office building, located in downtown Los Angeles. Results of this study indicate that the approach not only yields identification results that match well-known global (linear) system identification methods, such as NExT/ERA, but it also provides additional benefits that global identification approaches suffer from. These benefits include: (1) enhanced sensitivity to small structural parameter changes, (2) ability to provide location information about the region in the large structure in which damage has occurred, and (3) not assuming that the underlying structure is linear. Thus, the approach is capable of detecting, quantifying, and classifying changes, when they do occur, if the actual building is subjected to strong earthquake ground motion.