| BP神经网络在润滑油摩擦改进剂复配性研究中的应用 |
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| 引用本文： | 马林才 侯仲淼. BP神经网络在润滑油摩擦改进剂复配性研究中的应用[J]. 河北理工学院学报, 2004, 26(1): 43-47 |
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| 作者姓名： | 马林才 侯仲淼 |
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| 作者单位： | [1]浙江交通职业技术学院汽车工程系，浙江杭州31112 [2]上海石油商品应用研究所，上海，200226 |
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| 摘 要： | 研制润滑油的关键问题之一是研究其中多种添加剂间的相互作用和添加剂间的最佳复配比。以正交试验设计为基础的直现分析和回归分析可以探讨添加剂间的相互作用，而基于上述方法的最佳复配比的计算往往误差较大。采用BP神经网络计算最佳复配比，并与前两种方法作比较，发现BP神经网络在计算最优复配比时，结论可靠，精度高，是研制最佳润滑油配方的优秀数学工具。
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| 关 键 词： | BP神经网络 润滑油摩擦改进剂 复配性研究 回归分析 |
| 文章编号： | 1007-2829(2004)01-0043-05 |
| 修稿时间： | 2003-06-14 |
The application of BP neural network in studying lubricating oil friction modifier additives compatibility |
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| MA Lin-cai,HOU Zhong-miao. The application of BP neural network in studying lubricating oil friction modifier additives compatibility[J]. Journal of Hebei Institute of Technology, 2004, 26(1): 43-47 |
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| Authors: | MA Lin-cai HOU Zhong-miao |
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| Abstract: | One of the key points in developing lubricating oil is studying the interaction and optimum ratio be- tween oil additives. Drirect analytics based on orthogonal experimental design and the regression analytics can be used to study the interaction between additives, while the optimum ratios between additives calculated respectively by this two methods are not accurate enough. The BP Neural Network, therefore, is adopted to solve this problem. Compared with the former two methods,the BP Neural Network is found to be the excellent mathematic tool in calculating the optimum ratio to give the reliable and accurate conclusion. |
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| Keywords: | lubrication oil regression analysics compatibility BP Neural |
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