Neuro-wavelet damage detection technique in beam, plate and shell structures with experimental validation

The paper presents a new neuro-wavelet damage detection technique for structural health monitoring. The proposed method combines the ability of the continuous wavelet transform to detect abnormalities in the structure dynamic parameters with the artificial neural network possibility of learning, remembering and recognition. The effectiveness of the method is verified on experimental mode shapes of a beam, plate and shell structures. The results of the study show that the neural network trained on the data from a simple structure can effectively improve the search of the location of the same type of damage in complex structures.