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对纤维缠绕环氧树脂基复合材料压力容器加压，可以得到声发射振幅分布数据，从而建立起此类容器爆破压力的预测模型。可用一个反向传递人工神经网络预测其爆破压力，实验证明，该方法的预测误差在5％以内。
The fiber-wound epoxy composite pressure vessel can be pressurized to obtain the acoustic emission amplitude distribution data to establish the prediction model of the burst pressure of such vessels. A back propagation artificial neural network can be used to predict the burst pressure. Experiments show that the prediction error of this method is within 5%.