Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization  

裂解气压缩机性能预测及其在过程优化中的应用(英文)

作　　者：李绍军 李凤 

机构地区：[1]Key Laboratory of Advanced Control and Optimization for Chemical Processes(East China University of Science and Technology),Ministry of Education

出　　处：《Chinese Journal of Chemical Engineering》2012年第6期1089-1093,共5页中国化学工程学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China (20976048, 21176072);the Fundamental Research Funds for the Central Universities

摘　　要：Cracking gas compressor is usually a centrifugal compressor. The information on the performance of a centrifugal compressor under all conditions is not available, which restricts the operation optimization for compressor. To solve this problem, two back propagation (BP) neural networks were introduced to model the performance of a compressor by using the data provided by manufacturer. The input data of the model under other conditions should be corrected according to the similarity theory. The method was used to optimize the system of a cracking gas compressor by embedding the compressor performance model into the ASPEN PLUS model of compressor. The result shows that it is an effective method to optimize the compressor system.Cracking gas compressor is usually a centrifugal compressor. The information on the performance of a centrifugal compressor under all conditions is not available, which restricts the operation optimization for compressor. To solve this problem, two back propagation （BP） neural networks were introduced to model the performance of a compressor by using the data provided by manufacturer. The input data of the model under other conditions should be corrected according to the similarity theory. The method was used to optimize the system of a cracking gas compressor by embedding the compressor performance model into the ASPEN PLUS model of compressor. The result shows that it is an effective method to optimize the compressor system.

关 键 词：COMPRESSOR characteristic curve NEURAL-NETWORK MODELING 

分 类 号：TQ051.21[化学工程]