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基于相似规律和神经网络的多级多相混输泵气液增压性能预测

常亮 杨晨宇 苏筱斌 戴晓宇 徐强 郭烈锦

常亮, 杨晨宇, 苏筱斌, 戴晓宇, 徐强, 郭烈锦. 基于相似规律和神经网络的多级多相混输泵气液增压性能预测[J]. 应用数学和力学, 2023, 44(6): 619-628. doi: 10.21656/1000-0887.430405
引用本文: 常亮, 杨晨宇, 苏筱斌, 戴晓宇, 徐强, 郭烈锦. 基于相似规律和神经网络的多级多相混输泵气液增压性能预测[J]. 应用数学和力学, 2023, 44(6): 619-628. doi: 10.21656/1000-0887.430405
CHANG Liang, YANG Chenyu, SU Xiaobin, DAI Xiaoyu, XU Qiang, GUO Liejin. Prediction of Gas-Liquid Pressurization Performances of Multistage Multiphase Pumps Based on Similarity Laws and Neural Networks[J]. Applied Mathematics and Mechanics, 2023, 44(6): 619-628. doi: 10.21656/1000-0887.430405
Citation: CHANG Liang, YANG Chenyu, SU Xiaobin, DAI Xiaoyu, XU Qiang, GUO Liejin. Prediction of Gas-Liquid Pressurization Performances of Multistage Multiphase Pumps Based on Similarity Laws and Neural Networks[J]. Applied Mathematics and Mechanics, 2023, 44(6): 619-628. doi: 10.21656/1000-0887.430405

基于相似规律和神经网络的多级多相混输泵气液增压性能预测

doi: 10.21656/1000-0887.430405
(我刊编委郭烈锦来稿)
基金项目: 

国家自然科学基金项目 51888103

详细信息
    作者简介:

    常亮(1991—),男,博士(E-mail: cl_013@stu.xjtu.edu.cn)

    通讯作者:

    郭烈锦(1963—),男,教授(通讯作者. E-mail: lj-guo@mail.xjtu.edu.cn)

  • 中图分类号: O303

Prediction of Gas-Liquid Pressurization Performances of Multistage Multiphase Pumps Based on Similarity Laws and Neural Networks

(Contributed by GUO Liejin, M. AMM Editorial Board)
  • 摘要: 准确预测多相混输泵的气液增压性能对油气生产的经济性和安全性至关重要.当前气液增压预测模型与方法存在参数范围窄、增压级数低的局限.该文搭建了工业参数级气液混输增压实验平台,实验获得了25级离心式混输泵的气液增压特性.提出了适用于高增压级数、变转速条件的混输泵气液增压性能预测方法.首先,构建了定转速、低增压级数混输泵气液增压人工神经网络;其次,采用相似规律,将变转速条件气液增压转换至设计转速条件;最后,基于等温压缩假设进行级间流动参数更新和高增压级数混输泵性能预测.不同级数(3~25级)和转速条件(2 500~3 500 r·min-1)混输泵气液增压预测的相对误差低于15%.该方法能够应用于其他类型多相混输泵的增压预测,为指导油气工业现场确定混输泵增压级数和生产评估提供有效方法.
    1)  (我刊编委郭烈锦来稿)
  • 图  1  多相混输泵气液增压实验系统

    Figure  1.  The gas-liquid pressurization experimental system for the multiphase pump

    图  2  多级多相混输泵与压力压差传感器布置

    Figure  2.  The structure of the multistage multiphase pump and the arrangement of differential pressure sensors

    图  3  混输泵气液两相增压特性[23]

      为了解释图中的颜色,读者可以参考本文的电子网页版本,后同.

    Figure  3.  Gas-liquid 2-phase pressurization performances in multiphase pumps[23]

    图  4  径向基函数神经网络结构

    Figure  4.  The structure of the radial basis function neural network

    图  5  不同入口含气率下,混输泵两相流量随增压级数的变化规律

    Figure  5.  Variations of the 2-phase flow rate of the multiphase pump with the stage number under different inlet gas volume fractions

    图  6  变转速条件三级混输泵气液两相增压相似的验证

    Figure  6.  Verification of similarity in gas-liquid pressurization under variable rotational speeds in a 3-stage multiphase pump

    图  7  变转速多级混输泵气液增压预测算法流程

    Figure  7.  The flow chart of the gas-liquid pressurization prediction algorithm for multistage multiphase pumps under variable speeds

    图  8  不同转速下,三级混输泵气液增压预测值与实验值比较

    Figure  8.  Comparison between the predicted and experimental values of gas-liquid pressurization performance of the 3-stage multiphase pump at different rotational speeds

    图  9  不同增压级数混输泵气液两相增压预测值与实验值比较

    Figure  9.  Comparison between the predicted and experimental values of gas-liquid pressurization performance of multiphase pumps with different stages

    表  1  实验参数范围

    Table  1.   Ranges of experimental parameters

    parameter range
    liquid mass flow rate mw/(kg·min-1) 133.3~433
    gas mass flow rate ma/(kg·min-1) 0~5.3
    inlet gas volume fraction λ/% 0~40
    inlet temperature Tm/℃ 15~30
    inlet pressure Pin/MPa 0.5
    rotational speed n/(r·min-1) 2 500, 3 000, 3 500
    下载: 导出CSV

    表  2  不同转速和增压级数混输泵气液增压平均预测相对误差

    Table  2.   The average relative errors for predicting gas-liquid pressurization performances of multiphase pumps with different stages under variable rotational speeds

    n/(r·min-1) 3 stages 9 stages 15 stages 21 stages
    3 500 2.7% 6.2% 7.6% 8.5%
    3 000 4.6% 7.5% 8.9% 12.5%
    2 500 4.5% 5.3% 8.2% 13.4%
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-12-30
  • 修回日期:  2023-02-20
  • 刊出日期:  2023-06-01

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