A Two Stage Damage Detection Method with Application to the Phrase I ASCE SHM Benchmark Building

Recently, a new method has been proposed by the authors for detecting structural local damage under limited input and output measurements. This method can be extended to detect structural local damage in complex structures based on substructure approach. In this paper, based on this structural damage detection and localization method, a two-stage damage detection strategy is developed with application to the ASCE SHM benchmark building to test its efficacy and provide a systemic solution to the Phase I benchmark problem for damage detection. In the first stage, an 8-DOF identification model is used to identify the floors and directions (X or Y) in which damages are present. Then, the detection is focused on the floors where damage occurs. A substructure approach is utilized for damage localization in the second stage. A 12-DOF identification model is used for the substructure containing the damaged structural floors to identify the exact locations of damage. Structural parameters and the unknown inputs are identified by a recursive algorithm based on sequential application of the Kalman extended estimator for the extended state vector and the least squares estimation for the unknown inputs. Only a limited number of measured acceleration responses of the benchmark structure subject to unmeasured excitation inputs are utilized. Damage detection results indicate that the new method can detect and localize various damage patterns of the benchmark problems with good accuracy.