Structural System Identification and Damage Detection using the Intelligent Parameter Varying Technique: An Experimental Study

Abstract

The unique capabilities of the intelligent parameter varying (IPV) technique for structural system identification and damage detection have been previously documented via comparative simulations. An intelligent parameter varying (IPV) approach for non-linear system identification of base excited structures. International Journal of Non-Linear Mechanics, 39(6), 993—1004; Saadat, S., Noori, M.N., Buckner, G.D., Furukawa, T.D. and Suzuki, Y. (2004). Structural health monitoring and damage detection using an intelligent parameter varying (IPV) technique. International Journal of Non-Linear Mechanics, 39(10), 1687—1697). These simulations demonstrate the effectiveness of IPV in detecting the existence and location of damage in base excited structures, and conclude that accuracy is not compromised by the introduction of realistic structural nonlinearities and ground excitation characteristics. This study presents an experimental verification of the IPV technique for structural system identification and damage detection. A scaled three-story, base-excited structure is designed and fabricated for these experiments. The structure is excited using a displacement-controlled shake table, and damage is introduced by triggering the release of cross-bracing tendons, i.e., inducing sudden changes in the restoring forces. Experimental results using harmonic and recorded earthquake excitation data clearly demonstrate the effectiveness of this IPV technique.

Keywords

structural health monitoring system identification damage detection base-excited structures artificial neural networks

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