Appliance of Elman neural networks in damage diagnosis of radial gate

Damage diagnosis and health monitoring of large-scale structures are becoming a hot research subject in the present structural engineering circle. Elman neural network is presented to identify and locate the crack damage of a radial gate located in the middle reaches of the main stream of the Jialing River. This method is an aggregation neural networks and pattern identification. And also make the combined index as input data of Elman neural networks, and make the damaged locations and degree as output data. Numerical simulation results show that Elman neural network method can make a better diagnosis for single and multiple damage identification.