In order to be able to determine the location and degree of bridge structural damage more accurately and efficiently,this paper proposes a new method for damage identification of continuous girder bridges based on salp swarm algorithm optimization support vector ma-chine method.This study proposes a novel approach for damage identification,utilizing the curvature mode difference as a highly sensitive index.The salp swarm algorithm(SSA)is employed to optimize the parameters of the Support Vector Machine(SVM)and establish the SVM prediction model.Numerical simulations are conducted using a finite element model of a three-span continuous girder bridge,with the vulnerable area of the bridge as the target for damage identification.The study demonstrates that employing curvature modal difference as a damage identification index effectively localizes and assesses the damage degree of bridge unit placement and multi-location damage.Additionally,the SSA-SVM model,with automatic parameter optimization,exhibits superior prediction accuracy compared to the conventional SVM model.
维普
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