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Magnetorheological elastomer (MRE) base isolator is a new semi-active control device that has recently acquired more attention. This paper proposes a new model for MRE base isolator to portray the nonlinear hysteresis between generated force and the displacement. In this model, a hyperbolic expression is proposed to compare with the classical Bouc-Wen model, which includes internal dynamics represented by a nonlinear differential equation. For the identification of model parameters, a modified artificial fish swarm algorithm is adopted using the experimental forcedisplacement/velocity data under different testing conditions. In this algorithm, a self-adaptive method for adjusting the algorithm parameters is introduced to improve the result accuracy. Besides, the behaviours in the algorithm are simplified to descend the algorithmic complexity. Parameter identification results are included to demonstrate the accuracy of the model and the effectiveness of the identification algorithm.

This paper presents a vibration-based structural health monitoring (SHM) technique for the identification of damage in a concrete arch beam replica section of the Sydney Harbour Bridge. The proposed technique uses residual frequency response functions (FRFs) combined with principal component analysis (PCA) to form a damage specific feature (DSF) that is used as an input parameter to artificial neural networks (ANNs). Extensive laboratory testing and numerical modelling are undertaken to validate the method. In the proposed technique, FRFs are obtained by the standard modal testing and damage is identified using ANNs that innovatively map the DSF to the severity of damage (length of damage cut). The results of the experimental and numerical validation show that the proposed technique can successfully quantify damage induced to a concrete arch beam simulating a real life structural component of the Sydney Harbour Bridge.