Statistical detection of structural damage based on model reduction |
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Authors: | Tao Yin Heung-fai Lam Hong-ping Zhu |
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Institution: | 1. Department of Building and Construction;City University of Hong Kong,Hong Kong,P.R.China 2. School of Civil Engineering and Mechanics,Huazhong University of Science and Technology,Wuhan 430074,P.R.China |
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Abstract: | This paper proposes a statistical method for damage detection based on the finite element (FE) model reduction technique that utilizes measured modal data with a limited number of sensors.A deterministic damage detection process is formulated based on the model reduction technique.The probabilistic process is integrated into the deterministic damage detection process using a perturbation technique,resulting in a statistical structural damage detection method.This is achieved by deriving the firstand second-order partial derivatives of uncertain parameters,such as elasticity of the damaged member,with respect to the measurement noise,which allows expectation and covariance matrix of the uncertain parameters to be calculated.Besides the theoretical development,this paper reports numerical verification of the proposed method using a portal frame example and Monte Carlo simulation. |
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Keywords: | damage detection model reduction perturbation technique Monte Carlo simulation |
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