Cantilever beams with defects in different locations are studied in the finite element software. The acceleration response of the cantilever beams is processed by the shock-waveform decomposition method in which the characteristic parameters of the acceleration are extracted, and the dataset is formed. Then, the dataset is trained by BP (Back Propagation) neural network to identify the location of defect. It is shown that the defect detection method based on the shock-waveform decomposition method and BP neural network has high defect detection accuracy and efficiency.
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