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

被引：5

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

来源：

CHINESE JOURNAL OF CHEMICAL ENGINEERING | 2012年 / 20卷 / 06期

基金：

中国国家自然科学基金;

关键词：

compressor; characteristic curve; neural-network; modeling; MAP GENERATION;

D O I：

10.1016/S1004-9541(12)60591-6

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

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.

引用

页码：1089 / 1093

页数：5

共 50 条

[31] Optimization of a Typical Gas Injection Pressurization Process in Underground Gas Storage [J].

Chen, Shuangqing ;

Yu, Ze ;

Li, Yuchun ;

Wang, Zhihua ;

Si, Minglin .

SUSTAINABILITY, 2024, 16 (20)

[32] A Deep Gaussian Process-Based Flight Trajectory Prediction Approach and Its Application on Conflict Detection [J].

Chen, Zhengmao ;

Guo, Dongyue ;

Lin, Yi .

ALGORITHMS, 2020, 13 (11) :1-19

[33] Optimum loss models for performance prediction of supercritical CO2 centrifugal compressor [J].

Cho, Seong Kuk ;

Son, Seongmin ;

Lee, Jekyoung ;

Lee, Si-Woo ;

Jeong, Yongju ;

Oh, Bong Seong ;

Lee, Jeong Ik .

APPLIED THERMAL ENGINEERING, 2021, 184

[34] Improved Error-Based Ensemble Learning Model for Compressor Performance Parameter Prediction [J].

Miao, Xinguo ;

Liu, Lei ;

Wang, Zhiyong ;

Chen, Xiaoming .

ENERGIES, 2024, 17 (09)

[35] Prediction of engine performance under compressor inlet flow distortion using streamline curvature [J].

Pachidis, Vassilios ;

Pilidis, Pericles ;

Templalexis, Ioannis ;

Alexander, Theodosios ;

Kotsiopoulos, Petros .

PROCEEDINGS OF THE ASME TURBO EXPO 2006, VOL 4, 2006, :279-295

[36] Methodology for a Numerical Multidimensional Optimization of a Mixer Coupled to a Compressor for Its Integrationin a Hyperloop Vehicle [J].

Galindo, Jose ;

Dolz, Vicente ;

Navarro, Roberto ;

Pallas, Borja ;

Torres, German .

APPLIED SCIENCES-BASEL, 2022, 12 (24)

[37] Performance Analysis of Gas Turbine Using Compressor Extraction in Compressed air System of Station [J].

Guo Xiaolei .

2020 5TH INTERNATIONAL CONFERENCE ON MECHANICAL, CONTROL AND COMPUTER ENGINEERING (ICMCCE 2020), 2020, :559-569

[38] Modeling and optimization of a fluidized catalytic cracking process under full and partial combustion modes [J].

Han, IS ;

Riggs, JB ;

Chung, CB .

CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2004, 43 (08) :1063-1084

[39] Numerical and experimental analyses of intake silencer and its effects on turbocharger compressor performance [J].

Liu, Chen ;

Cao, Yipeng ;

Liu, Yang ;

Zhang, Wenping ;

Ming, Pingjian ;

Ding, Sihui .

ADVANCES IN MECHANICAL ENGINEERING, 2019, 11 (03)

[40] Performance evaluation and optimization of a novel heat pump clothes dryer with ESD-compressor [J].

Liu, Shuailing ;

Ma, Guoyuan ;

Jiang, Yuepeng ;

Li, Xiang ;

Xu, Shuxue ;

Wu, Junfeng .

INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2024, 157

← 1 2 3 4 5 →