Damage Severity Assessment Using Modified BP Neural Network

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Damage severity identification is an important content among structural damage identification. In order to avoid the disadvantages of conventional BPNN, a modified BP neural network was proposed to identify structural damage severity in this paper. The modified BPNN was trained by using structural modal frequency qua BPNN input, and then used to forecast structural damage severity. Finally, the results of simulation experiment of composite material cantilever girder show that the improved method is very effective for damage severity identification and possess great applied foreground.