Damage localization of structures identified with deterministic-stochastic models using seismic data

In earthquake prone area, development of promising Structural Health Monitoring (SHM) systems to efficiently assess the integrity of critical structures right after the strike of an earthquake is desired. System identification plays a key role to the success of a SHM system. The dynamic model considered in the identification process must provide representative realization of the structure while taking into account the uncertainty of measurement error and noise. A deterministic-stochastic subspace identification method is adopted in this study to identify the equivalent SIMO system parameters of the discrete-time state equation. The method of damage locating vector (DLV) is then considered for damage detection. Members (or stories) with nearly zero stress under the static loadings of DLVs are considered potentially damaged, whereas the DLVs are derived from singular value decomposition of the flexibility differential of the structure before and after the damage state. A series of shaking table tests has been conducted using a five-story model frame as the objective to explore the feasibility of the proposed methodology. Wireless sensing devices have been employed in the tests to measure the ground and floor accelerations of the structure. Experimental results indicate that the proposed scheme proves effective and robust, regardless of full or partial observations, at a single damage condition under non-stationary seismic input excitations. It is yet insufficient for multiple damage conditions and needs further study.