A Hilbert Transform Method for System Identification of Time-Varying Building Structures
This paper presents a Hilbert transform method for the time-varying property identification of high-rise buildings with limited sensor deployments in combination with an observer technique and a branch-and-bound technique. The observer technique is introduced to estimate building responses from the limited measurements. This estimation depends upon the current/damaged condition of buildings to be identified. As such, the branch-and-bound technique is used to develop potential damage scenarios and pinpoint the specific damage scenario that minimizes a global error index of stiffness and damping coefficients while limiting the local error of each story into less than a predetermined threshold. A 60-story shear building with abruptly varying stiffness at multiple stories is used as an example. Numerical results indicate that the proposed method can accurately detect locations and variations of the structural properties of the building with limited sensors deployed at appropriate locations. Additional research indicated insignificant effects of noise and successful detections of damage at adjacent stories.
Z. Wang and G. Chen, "A Hilbert Transform Method for System Identification of Time-Varying Building Structures," Proceedings of the 5th International Conference on Structural Health Monitoring of Intelligent Infrastructure (2011, Cancun, Quintana Roo, Mexico), International Society for Structural Health Monitoring of Intelligent Infrastructure (ISHMII), Dec 2011.
5th International Conference on Structural Health Monitoring of Intelligent Infrastructure (2011: Dec. 11-15, Cancun, Quintana Roo, Mexico)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Branch And Bounds; Building Structure; High Rise Building; Hilbert Transform; Numerical Results; Property Identification; Stiffness And Damping Coefficients; Varying Stiffness; Numerical Methods; Sensors; Stiffness; Structural Health Monitoring; Tall Buildings; Damage Detection
Article - Conference proceedings
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01 Dec 2011