Research on structural damage identification of bridge engineering based on dynamic parameters

The occurrence of structural damage will affect the bridge structural dynamic characteristics, and the scientific identification of structural damage in bridge engineering not only helps to repair and extend the use of time limit, but also relates to public safety. In this paper, based on the frequency change and flexibility curvature modal change, combined with artificial neural network, a bridge damage identification method based on RBF neural network is designed. And the finite element model is established to simulate the arch bridge and simply supported girder bridge as an example, to explore the accuracy of different combinations of structural damage identification in bridge engineering. It is found that with the intrinsic frequency, frequency combination, curvature, and curvature-frequency combination as the input items, the accuracy of damage identification of arch bridges by this paper’s method is 78%, 71.6%, 76.5%, and 81.5%, which reflects a good level. The application of the bridge damage identification method in this paper can make an accurate judgment of structural damage, and can make a quantitative analysis of the degree of damage, and the relative error of the analysis results is kept within 5%. This paper provides a new perspective for bridge engineering structural damage identification.