| 热镀锌过渡卷的力学性能预测 |
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| 引用本文： | 林传华,张宝平,周旭东.热镀锌过渡卷的力学性能预测[J].宝钢技术,2005(6):31-34. |
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| 作者姓名： | 林传华 张宝平 周旭东 |
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| 作者单位： | 1. 宝钢股份公司,上海,200941
2. 河南科技大学,河南,洛阳,471003 |
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| 摘 要： | 在收集大量现场数据的基础上,运用BP神经网络算法,建立了退火处理各工艺参数对热镀锌过渡卷力学性能影响的数学模型,并与线性回归模型相比较.结果表明,BP算法预测误差较线性回归预测误差小;神经网络用于热镀锌过渡卷力学性能预测是可行的.
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| 关 键 词： | 热镀锌 退火 BP算法 力学性能 性能预测 |
| 文章编号： | 1008-0716(2005)06-0031-04 |
| 修稿时间： | 2004年12月23日 |
Prediction of Mechanical Properties of Hot Dip Galvanized Transition Strip |
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| LIN Chuan-hua,ZHANG Bao-ping,ZHOU Xu-dong.Prediction of Mechanical Properties of Hot Dip Galvanized Transition Strip[J].Baosteel Technology,2005(6):31-34. |
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| Authors: | LIN Chuan-hua ZHANG Bao-ping ZHOU Xu-dong |
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| Abstract: | Based on a lot of collected data on-site, with algorithm of BP artificial neural net, a mathematical model for effect of technological parameters for annealing treatment on mechanical properties of hot dip galvanized strip has been developed and compared with the multi-variant linear regression model. Results show that there are fewer errors by BP artificial neural net than that by multi-variant linear regression model. It is possible that the BP neural net can be applied to the prediction of mechanical properties of hot dip galvanized transition strip. |
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| Keywords: | hot dip galvanizing annealing BP algorithm mechanical property property prediction |
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