Damage identification for beams using ANN based on statistical property of structural responses

In this paper, a novel method of damage identification for beam using artificial neural network (ANN) based on statistical properties of structural dynamic responses is developed. In this method, the changes of variances (or covariance) of structural responses are selected as damage indices for damage identification. Firstly, the feasibility of using the statistical property as damage index is validated theoretically with sensitivity analysis. Then the back-propagation ANN with the change of variance of structural response as input and damage status as output is adopted for identifying the damage in beams. The damage identification for a three-span continuous beam using the developed method is numerically simulated. From the results of numerical simulation in both single damage case and multi-damage case, it is found that the ANN with the statistical property as damage index can correctly detect the damage location and identify the damage extent with high precision. Finally, the conclusion is given that the novel method using the statistical property of structural response as damage index for damage identification is feasible and efficient.