Application of Distributed Network in Bridge Structure Safety Inspection

Abstract

In order to solve the problems of the monitoring and health assessment of the main structure of bridges, and to provide technical support for the bridge from the regular inspection to the predictive maintenance mode, a distributed network is proposed for the safety inspection of bridge structures. Through the numerical simulation of the bridge, the finite element model is established and the modal analysis is carried out to obtain the modal data before and after the damage. The damage index of the bridge structure is taken as the input and output variables after the curvature of the modal data, and the nonlinear mapping relationship between the input variables and output variables is established. A large amount of damage modal data is randomly formed into the training set and the test set, and the training set is used to train the neural network. The training accuracy is set to 10−3, and the learning rate is set to 0.01. The test set data is used to identify the damage to the neural network after the training. The experimental results show that the developed program is more accurate in identifying the damage position of the simply supported beam and the continuous beam, and the fitting degree between the predicted value and the real value of the damage degree of the structure can reach 0.97. It is concluded that the damage identification program can intelligently identify and predict two common types of bridge structural damage, namely, the simply supported beam and the continuous beam. And the identification effect is good and has certain feasibility.