computationally efficient delamination detection in composite beams using haar wavelets

the paper presents an integrated vibration-based method for delaminations detection in homogeneous and composite beams. the method is based on haar wavelets and artificial neural networks (anns). firstly, scaled modal responses of the structure are expanded into haar series by chen–hsiao method (chm), and a delamination feature index is constructed. the database of 68 datasets built on haar wavelet and frequency-based approaches was utilized by different anns to establish the mapping relationship between the delamination status and the delamination feature index or frequencies. the results are compared to each other. the simulations show the proposed complex method with delamination index detects the location of delaminations and identifies the delamination extent with high precision (>90%); the approach requires less computations and processing time than the frequency-based approach.