| 基于因素分析的复合神经网络及其在软测量中的应用 |
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| 引用本文： | 李勇刚,桂卫华,陈峰.基于因素分析的复合神经网络及其在软测量中的应用[J].信息与控制,2004,33(2):141-144,150. |
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| 作者姓名： | 李勇刚 桂卫华 陈峰 |
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| 作者单位： | 中南大学信息科学与工程学院,湖南,长沙,410083 |
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| 基金项目： | 国家 8 63计划资助项目 (2 0 0 1AA4110 40)，国家 973计划资助项目 (2 0 0 2CB3 12 2 0 0 ) |
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| 摘 要： | 针对工业生产中,众多因素对生产影响程度不同的特点,提出了一种基于因素分析的复合神经网络(FA-MNN)模型.介绍了FA-MNN模型的结构,改进了神经网络的学习算法,并将其应用于氧化铝高压溶
出过程中苛性比值及溶出率的软测量,利用现场实际运行数据进行仿真,结果表明FA-MNN模型能有效实现苛性比值及溶出率的在线检测.
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| 关 键 词： | 因素分析 复合神经网络 软测量 苛性比值 溶出率 |
| 文章编号： | 1002-0411(2004)02-0141-04 |
Multiple Neural Networks Based on Factor Analysis and its Application in Soft Sensor |
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| LI Yong gang,GUI Wei hua,CHEN Feng.Multiple Neural Networks Based on Factor Analysis and its Application in Soft Sensor[J].Information and Control,2004,33(2):141-144,150. |
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| Authors: | LI Yong gang GUI Wei hua CHEN Feng |
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| Abstract: | Considering the fact that a large number of factors influence the industry process and their influence varies, a multiple neural networks (FA MNN) model based on factor analysis is proposed. The structure of FA MNN is introduced and its learning algorithm is improved. The FA MNN model is applied in the process of high pressure digestion of alumina. Simulation results show that the FA MNN model can sense the ratio of soda to aluminate and leaching rate online effectively. |
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| Keywords: | factor analysis multiple neural networks (MNN) soft sensor ratio of soda to aluminate (RSA) leaching rate(LR) |
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