文献类型：会议论文

英文题名：Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization

作者：Li Shaojun[1];Li Feng[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

会议论文集：23rd Chinese Process Control Conference (CPCC)

会议日期：AUG 11-12, 2012

会议地点：Xiamen, PEOPLES R CHINA

语种：英文

外文关键词：compressor; characteristic curve; neural-network; modeling

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.