Damage identification method of prestressed concrete beam bridge based on convolutional neural network

Bridges play an important role in transportation, but because of overload and natural factors, bridges will inevitably be damaged, which will affect traffic and even lead to major accidents. Therefore, timely and accurate identification of bridge damage is extremely necessary. Because of the great danger of manual detection, in order to identify the damage of prestressed concrete girder bridge safely, conveniently and accurately, this paper proposes a method of damage identification of prestressed concrete girder bridge based on convolutional neural network, which realizes the intelligent identification of bridge damage. Firstly, the damage identification method based on the flexibility matrix is introduced, and the flexibility diagonal curvature index constructed by the diagonal element of flexibility matrix is introduced. Secondly, the basic principle of applying convolutional neural network to bridge damage identification is elaborated. Finally, combined with the flexibility curvature method and the convolutional neural network, the flexibility of the structure is selected as the input of the convolutional neural network to realize the bridge damage identification. Through simulation, it is found that the use of convolutional neural network for the bridge identification is feasible, and combined with the flexibility curvature method, it can well identify the damage location and damage degree of prestressed concrete beam bridge structure.