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| 基于神经网络-遗传算法优化柴油机油台架试验 | |
| 引用本文： | 李为民,徐春明,许志伟.基于神经网络-遗传算法优化柴油机油台架试验[J].润滑与密封,2006(4):81-83. |
| 作者姓名： | 李为民 徐春明 许志伟 |
| 作者单位： | 1. 中国石油大学(北京)重质油国家重点实验室,北京,102200;江苏工业学院化工系,江苏,常州,213016 2. 中国石油大学(北京)重质油国家重点实验室,北京,102200 3. 香港科技大学化工系,香港 |
| 摘 要： | 根据15W/40 CD柴油机油的模拟实验与台架试验的基础数据,用人工神经网络(ANN)的反向传播算法建立了模拟实验与台架试验神经网络预测模型,该神经网络模型合适的拓扑结构为5-7-1,学习速率为0.2,动量因子为0.9。探讨了用模拟实验数据预测台架试验结果的可能性,检验证明用人工神经网络方法建立的模型能准确预报15W/40CD柴油机油的台架试验结果。该神经网络预测模型用遗传算法优化,得到了15W/40 CD级柴油机油能通过台架试验的最优模拟实验结果。 |
| 关 键 词： | 柴油机油 模拟实验 台架试验 神经网络 遗传算法 |
| 文章编号： | 0254-0150(2006)4-081-3 |
| 收稿时间： | 2005-05-23 |
| 修稿时间： | 2005年5月23日 |
Optimization for Engine Test of Engine Oil Based on Genetic Algorithm-neural Network |
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| Li Weimin,Xu Chunming,Chi HuiWai.Optimization for Engine Test of Engine Oil Based on Genetic Algorithm-neural Network[J].Lubrication Engineering,2006(4):81-83. | |
| Authors: | Li Weimin Xu Chunming Chi HuiWai |
| Affiliation: | 1. State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing 102200, China; 2. Department of Chemical Engineering, Jiangsu Polytechnic University, Changzhou Jiangsu 213016, China ; 3. Department of Chemical Engineering, Hong Kong University of Science and Technology, Hong Kong, China |
| Abstract: | Based on the data of bench test and engine test of 15W/40 CD grade engine oil,an artificial neural network(ANN) model was developed for predicting the relationship between engine test and bench test using back-propagation algorithm.The appropriate topology of ANN was 5-7-1.The learning rate of ANN was 0.2,and the momentum factor of ANN was 0.3.It is shown that the ANN model can correlate and predict results of engine test of 15W/40 CD grade engine oil with much accuracy.The ANN model was optimized by incorporating genetic algorithm.Optimal bench test of 15W/40 CD grade engine oil was obtained using the ANN model developed. |
| Keywords: | diesel engine oil bench test engine test artificial neural network genetic algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |