| 胡晖,邬慧雄,徐世民,李鑫钢.用人工神经网络预测催化精馏塔开工过程的研究[J].分子催化,2006,(4):360-362 |
| 用人工神经网络预测催化精馏塔开工过程的研究 |
| Predictions Catalytic Distillation Column Start-up Processes Via Artificial Neural Network |
| 投稿时间：2005-07-26 修订日期：2005-09-26 |
| DOI： |
| 中文关键词: 人工神经网络,催化精馏,开工,预测模型 |
| 英文关键词:Artificial neural network,Catalytic distillation,Start-up,Prediction model |
| 基金项目: |
| 胡晖 邬慧雄 徐世民 李鑫钢 |
福州大学化学化工学院 福州350002(胡晖)
，清华大学化学工程系 北京100084(邬慧雄)
，天津大学精馏技术国家工程研究中心 天津300072(徐世民，李鑫钢)
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| 摘要点击次数: 1128 |
| 全文下载次数: 49 |
| 中文摘要: |
| 催化精馏是使化学反应过程和精馏分离过程结合在一起,是伴有化学反应的新型特殊精馏过程.“反应精馏”概念自20年代提出以来,从30年代到60年代初,研究都是对特定体系的工艺探索;70年代后,研究扩展到非均相催化反应体系,出现了非均相催化精馏过程,成为了反应精馏的一个重要分支; |
| 英文摘要: |
| The time consumed in starting up the distillation unit with appreciable holdups can be an important fraction of the total distillation time,particular for catalytic distillation systems with large holdups.To optimize the whole process,the start-up period has to be considered as a part of the complete catalytic distillation process.In this paper,BP artificial neural network model was presented as a tool to estimate the start-up process for a given catalytic distillation system.It can been seen that through the examination of the case studied in this work,a good start-up policy can reduce both the energy and time requirements in the start-up phase of catalytic distillation processes.The results based on 20 start-up policies showed that the time consumed in start-up period with an average error of 4.140% and a maximum error of 10.291% for the case studied in this work.The accuracy of the model will depend upon the data available and the type of model. |
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