| 应用 BP 神经网络预测精锻斜齿轮损伤因子 |
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| 引用本文： | 冯玮,曹继昌,吴舒婷,李扬帆.应用 BP 神经网络预测精锻斜齿轮损伤因子[J].武汉理工大学学报(信息与管理工程版),2014(3):328-331. |
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| 作者姓名： | 冯玮 曹继昌 吴舒婷 李扬帆 |
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| 作者单位： | 武汉理工大学材料科学与工程学院,湖北武汉430070 |
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| 基金项目： | 中央高校基本科研业务费专项资金资助项目（2013-IV-012）． |
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| 摘 要： | 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。
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| 关 键 词： | 斜齿轮精锻 损伤因子 BP神经网络 数值模拟 |
Application of BP Neural Network in Damage Factor Prediction for Precision Forging Helical Gears |
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| FENG Wei,CAO Jichang,WU Shuting,LI Yangfan.Application of BP Neural Network in Damage Factor Prediction for Precision Forging Helical Gears[J].Journal of Wuhan University of Technology(Information & Management Engineering),2014(3):328-331. |
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| Authors: | FENG Wei CAO Jichang WU Shuting LI Yangfan |
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| Affiliation: | FENG Wei, CAO Jichang, WU Shuting, LI Yangfan |
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| Abstract: | 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 . |
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| Keywords: | precision forging helical gears damage factor BP neural network numerical simulation |
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