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6061铝合金在热变形时稳态应力主要受应变、温度、应变速率的影响。为了提高稳态应力的预测精度,基于Sellars-Tegart本构方程和BP神经网络建立了6061铝合金的预测模型,对比和分析了两个模型的预测效果。结果表明,两个预测模型得到的预测值均与试验值吻合程度较高,可较好地描述稳态应力与各热力参数之间的非线性关系,而且通过决定系数和标准残差的对比证实了BP神经网络预测模型具有更高的预测精度。
Steady-state stress of 6061 aluminum alloy during hot deformation is mainly affected by strain, temperature and strain rate. In order to improve the prediction accuracy of steady state stress, a prediction model of 6061 aluminum alloy was established based on Sellars-Tegart constitutive equation and BP neural network. The prediction results of two models were compared and analyzed. The results show that the predicted values obtained by the two prediction models are in good agreement with the experimental values and can well describe the nonlinear relationship between the steady-state stress and each thermodynamic parameter, and confirm the comparison between the decision coefficient and the standard residuals The BP neural network prediction model has higher prediction accuracy.