基于BP神经网络的理论,建立了多应力水平下T91钢蠕变速率预测模型。通过实验采集到了相关实验结果,利用建立的BP神经网络模型,对实验结果数据进行训练。结果表明:模拟结果与实测结果吻合良好,预测精度很高;采用BP神经网络法可为研究T91钢蠕变行为提供一条可行方法,根据该模型可改善材料的工艺。 Based on the theory of BP neural network, a prediction model of creep rate of T91 steel under multi-stress level is established. Relevant experimental results were collected through experiments, and the BP neural network model was established to train the experimental data. The results show that the simulation results are in good agreement with the measured results and the prediction accuracy is very high. Using BP neural network method can provide a feasible method for studying the creep behavior of T91 steel. According to the model, the material technology can be improved.