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《Journal of Earthquake Engineering and Engineering Vibration》 2008-04
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Structural damage detection based on EMD method and RBF neural network

CHENG Lei1,QU Weilian2(1.Research Institute of Structural Engineering and Disaster Reduction,Tongji University,Shanghai 200092,China;2.Hubei Key Laboratory ofRoadway Bridge and Structure Engineering,Wuhan University of Technology,Wuhan 430070,China)  
Aiming at three independent detection processes carried out according to certain order of sequence,identification,orientation and severity estimation of structural damage,a combination detection method that can carry out the above three processes simultaneously was put forward.Firstly,this method adopted the empirical mode decomposition(EMD) method to decompose the top-story seismic acceleration response of a three-story shear reinforced concrete building under several damage conditions into some intrinsic mode function(IMF) components.Then the damage identification vectors were constituted by using IMF components and original acceleration responses not decomposed by EMD method.Those damage identification vectors were used as input characteristic parameters for radial basic function neural network(RBFNN) to detect structural damage.The concrete step of this combination detection method was given,and the numerical simulation experiment demonstrated its feasibility and validity.
【Fund】: 国家自然科学基金项目(50378074)
【CateGory Index】: TU312.3
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