Vibration-based damage detection for composite structures using wavelet transform and neural network identification

This paper presents an integrated method for damage detection of composite structures using their vibration responses, wavelet transform and artificial neural networks (ANN) identification. Structural damage feature proxy vectors are constructed and calculated based on energy variation of the structural vibration responses decomposed using wavelet package before and after the occurrence of structural damage. The ANN are applied to establish the mapping relationship between structural damage feature proxy and damage status (location and severity). The results of crack damage detection for PVC sandwich plates show that the method developed in this paper can be applied to online structural damage detection and health monitoring for various industrial structures.