Near Real Time Hybrid System Identification Framework for Civil Structures with Application to Burj Khalifa
AbstractThis study proposes a near real time hybrid framework for system identification (SI) of structures using data from structural health monitoring systems. To account for both stationary/weakly nonstationary response under normal conditions (e.g. extratropical winds and/or ambient excitations) and transient/highly nonstationary response under transient events (e.g. earthquakes, windstorms, or time varying traffic loadings) a hybrid framework is introduced by integrating a new nonstationary SI scheme based on wavelets in tandem with transformed singular value decomposition, and a robust stationary SI scheme called covariance driven stochastic subspace identification. Extensive numerical simulations as well as analysis of full scale data are conducted to evaluate the efficacy of the scheme. To facilitate expeditious and convenient utilization of this framework in a practical application, a web enabled approach and its workflow concerning measurements of the world's tallest building, Burj Khalifa, ar.