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Recognition of Damage Acoustic Emission Signals of Fiberglassreinforced Plastic Based on a Wavelet Neural Network

In this paper, the wavelet neural network of a modern signal processing technique was used to recognize damage patterns. The wavelet analysis was found to have a good performance in the local time and frequency domains. It can reflect the damage of an FRP composite material and extract the feature information to recognize the three main injury patterns of FRP composite materials.

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