应用BP神经网络预测精锻斜齿轮损伤因子

Application of BP Neural Network in Damage Factor Prediction for Precision Forging Helical Gears

通过利用DEFORM-3D软件对斜齿轮精密锻造过程进行有限元模拟,获得了损伤因子的分布特点。运用Matlab软件建立BP神经网络损伤因子预测模型,分析了不同锻造条件对损伤因子的影响,并对不同锻造条件下的损伤因子进行预测。利用检测样本对训练的神经网络进行验证,结果表明,BP神经网络预测损伤因子与模拟结果吻合较好,预测结果误差较小,预测精度满足实际应用要求。

The precision forging finite element model for helical gear was established by DEFORM -3D to obtain the distribution characteristics of damage factor .The damage factor prediction model of BP neural network was established by MATLAB to predict influence of different forging conditions on the damage factor .The trained neural network was validated using test samples.The results show that the predicted results agree well with the simulated ones .The differences of prediction results exhibit low value;the predicted precision satisfies the request of industry .The trained BP neural network could be used to analyze the effect of different forging conditions on damage factor .