IDENTIFICATION OF DAMAGE LOCATION IN BRIDGE DECK BY NEURAL NETWORK

Identification of damage locations is an important step in damage detection for large-scale bridge structures. By taking the cable-stayed Kap Shui Mun Bridge as an example, a method of damage localization for bridge deck by pattern recognition technique of neural network is studied. Two kinds of networks, dynamic network and GA network, are used to investigate the feasibility of the method. For dynamic network, the network structure is constructed dynamically with training progress. For GA network, the genetic algorithm is introduced in network training. The recognition results by using the two networks are compared. The results show the feasibility of the proposed methods. Both networks can give a satisfactory result when a small number of parameters are inputted.