Analyses on structural damage identification based on combined parameters

The relative sensitivities of structural dynamical parameters were analyzed using a directive derivation method. The neural network is able to approximate arbitrary non-linear mapping relationship,so it is a powerful damage identification tool for unknown systems.A neural network-based approach was presented for the structural damage detection. The combined parameters were presented as the input vector of the neural network, which computed with the change rates of the several former natural frequencies (C), the change ratios of the frequencies (R), and the assurance criterions of flexibilities (A). Some numerical simulation examples, such as, cantilever and truss with different damage extends and different damage locations were analyzed.The results indicate that the combined parameters are more suitable for the input patterns of neural networks than the other parameters alone.