| 基于PLS-混合Pi-Sigma模糊神经网络模型的甲醇合成装置变换工序CO变换率软测量建模 |
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| 引用本文： | 程剑,宋淑群,张凌波,顾幸生.基于PLS-混合Pi-Sigma模糊神经网络模型的甲醇合成装置变换工序CO变换率软测量建模[J].医学教育探索,2015(1):66-71. |
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| 作者姓名： | 程剑 宋淑群 张凌波 顾幸生 |
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| 作者单位： | 华东理工大学化工过程先进控制和优化技术教育部重点实验室，上海 200237;1.华东理工大学化工过程先进控制和优化技术教育部重点实验室，上海 200237；2.兖矿集团国宏化工有限责任公司，山东 邹城 273500;华东理工大学化工过程先进控制和优化技术教育部重点实验室，上海 200237;华东理工大学化工过程先进控制和优化技术教育部重点实验室，上海 200237 |
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| 基金项目： | 中央高校基本科研业务专项资金：上海市重点学科项目(B504) |
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| 摘 要： | 煤制甲醇合成变换过程中，需要把原料气中的一部分CO变换成CO2与H2，以提高H2的含量。为了能够快速地得到CO的变换率，利用偏最小二乘在提取信息、去噪、精简数据等方面的优势，将其与混合Pi Sigma模糊神经网络进行了融合，建立了CO变换率预测模型。该模型仿真时间短且具有较高的精度，能够指导并调整甲醇合成净化气中的碳氢比。
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| 关 键 词： | 偏最小二乘 Pi Sigma神经网络 高木 关野模型 甲醇 |
| 收稿时间： | 2014/4/10 0:00:00 |
PLS-Hybrid Pi Sigma Fuzzy Neural Network Method and Its Application in Methanol Conversion Purification Process about CO Conversion Rate |
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| CHENG Jian,SONG Shu-qun,ZHANG Ling-bo and GU Xing-sheng.PLS-Hybrid Pi Sigma Fuzzy Neural Network Method and Its Application in Methanol Conversion Purification Process about CO Conversion Rate[J].Researches in Medical Education,2015(1):66-71. |
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| Authors: | CHENG Jian SONG Shu-qun ZHANG Ling-bo and GU Xing-sheng |
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| Institution: | 1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237,China; 2. Yankuang Guohong Chemical Industry Co. Ltd, Zoucheng 273500, Shandong, China;1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237,China; 2. Yankuang Guohong Chemical Industry Co. Ltd, Zoucheng 273500, Shandong, China;1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237,China; 2. Yankuang Guohong Chemical Industry Co. Ltd, Zoucheng 273500, Shandong, China;1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237,China; 2. Yankuang Guohong Chemical Industry Co. Ltd, Zoucheng 273500, Shandong, China |
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| Abstract: | In the process of methanol conversion purification, a portion of the carbon monoxide in the feed gas will be converted to carbon dioxide and hydrogen so as to enlarge the content of hydrogen. In order to control the conversion rate of carbon monoxide quickly, this paper integrates the advantages of the PLS (partial least squares) in extracting information, removing noise and streaming data with mixed Pi Sigma fuzzy neural network to establish a model of carbon monoxide conversion rate. The simulation results show that the proposed model has a quicker simulation speed and higher accuracy, and can guide and adjust the hydrocarbon ratio of purified gas in the methanol synthesis. |
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| Keywords: | partial least squares(PLS) Pi Sigma neural network Takagi Sugeno modal methanol |
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