The acoustic emission detection technology is used to position the acoustic emission source of 3D braided composite material. Through comprehensive utilization of the characteristic parameters of acoustic emission signals, the wavelet neural network (WNN) is used to conduct damage positioning and computation, and by combining the shuffled frog leaping algorithm (SFLA), it can improve the convergence performance. Through experiment comparison with traditional positioning computation method, after optimization with the frog leaping algorithm, the wavelet network acoustic emission source positioning method can effectively improve the precision of damage positioning.
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