流体机械

2021, v.49;No.585(03) 46-51

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基于多系统联合仿真的变负荷工况下往复压缩机动态特性研究
Study on dynamic characteristics of reciprocating compressor under variable load conditions based on multi-system co-simulation

张进杰;孙旭;江胜飞;
ZHANG Jinjie;SUN Xu;JIANG Shengfei;Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology,Beijing University of Chemical Technology;Beijing Key Laboratory of Health Monitoring Control and Fault Self-recovery for High-end Machinery,Beijing University of Chemical Technology;Shunan Gas Mine,PetroChina Southwest Oil & Gas Field Branch;

摘要(Abstract):

针对往复压缩机在气量调节工况下因多系统耦合、多参数关联导致工作模型复杂,对压缩机动态特性分析难度大的问题,本文提出了针对气量调节系统与压缩机的多系统联合仿真的建模方法,首先建立独立的调节系统各模块工作模型,利用不同模型对接端口完成子系统模型之间的数据交互,融合压缩机工作模型构建了变负荷工况下往复压缩机工作特性分析模型,将仿真数据与实测数据进行对比,证明了多系统联合仿真与传统仿真方式相比,能够更准确地表达变负荷工况下压缩机的动态特性。
In order to solve the problem of difficulty in analyzing the dynamic characteristics of reciprocating compressor due to complex working model caused by multi-system coupling and multi-parameter correlation under the condition of capacity control of reciprocating compressor,in this paper,a modeling method for multi-system co-simulation of capacity control system and compressor was proposed.Firstly,the independent working model of each module of the capacity control system was established,and then the data exchange between subsystem models was completed using different model docking ports.The working characteristic analysis model of the reciprocating compressor under variable load condition was constructed by combining the working model of the compressor.By comparing the simulation data with the measured data,it was proved that compared with the traditional simulation method,the multi-system co-simulation can more accurately express the dynamic characteristics of the compressor under variable load conditions.

关键词(KeyWords): 变负荷;往复压缩机;多系统;联合仿真
variable load conditions;reciprocating compressor;multi-system;co-simulation

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基金项目(Foundation): 国家重点研发计划项目(2016YFF0203305);; 压缩机技术国家重点实验室(压缩机技术安徽省实验室)开放基金项目(SKL-YSJ201808;SKL-YSJ201911)

作者(Author): 张进杰;孙旭;江胜飞;
ZHANG Jinjie;SUN Xu;JIANG Shengfei;Compressor Health and Intelligent Monitoring Center of National Key Laboratory of Compressor Technology,Beijing University of Chemical Technology;Beijing Key Laboratory of Health Monitoring Control and Fault Self-recovery for High-end Machinery,Beijing University of Chemical Technology;Shunan Gas Mine,PetroChina Southwest Oil & Gas Field Branch;

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