Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization<sup>*</sup>

李绍军; 李凤

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

Updated：2026-01-06

- Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization^*
- Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization^*
- 中国化学工程学报（英文版） 2012年20卷第6期页码：1089-1093
- Affiliations：
  
  Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology), Ministry of Education,Shanghai,China,200237
- Author bio：
- Funds：
  
  Supported by the National Natural Science Foundation of China (20976048;21176072);the Fundamental Research Funds for the Central Universities
- DOI：
  中图分类号：
- 纸质出版：2012
- Accepted：
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李绍军, 李凤. Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization^*[J]. 中国化学工程学报（英文版）, 2012,20(6):1089-1093.

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1089-1093.
李绍军, 李凤. Prediction of Cracking Gas Compressor Performance and Its Application in Process Optimization^*[J]. 中国化学工程学报（英文版）, 2012,20(6):1089-1093. DOI：

[J]. Chinese Journal of Chemical Engineering, 2012, 20(6): 1089-1093. DOI：

摘要

Abstract

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.

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