Structural Damage Identification Based on Combination of Modal Data Using Neural Networks

In this research, the combination of modal data is used to identify the damage of a FEM model using neural networks. The identification ability with different levels of noise and incomplete mode shapes are also investigated. It has been proved that the neural network using combination of modal parameters as input has a excellent identification ability with ideal error tolerance and robustness. Numberical example analyses on truss are presented to demonstrate the accuracy and efficiency of the proposed method.