Application of BP Artificial Neural Network in Structure Damage Identification

The application of the neural network in the structure damage identification is studied using a combination of theoretical and experimental methods. A multi-layer neural network models based on the BP algorithm is designed for the damage identification of existing model structure. The model is trained with the data from an engineering beam to filter different transfer function, train function and the unit number of hidden layer by contrast to determine the best network model for detect damage. At last, the model is used to detect the damage of cable-stayed bridge with an improved method of Data pre-processing using the square rate of change in Frequency as input date of network. The satisfied test result shows that the model is effective to reflect the injury status of the existing structure.