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基于响应面法的折流板除雾器分离性能优化

  • 马巍威 吴小林 姬忠礼
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  • 1. 中国石油大学(北京)化学工程学院,北京 102249
    2. 中国石油大学(北京)机械与储运工程学院,北京 102249
    3. 过程流体过滤与分离技术北京市重点实验室,北京 102249

收稿日期: 2017-10-18

  修回日期: 2018-01-15

  网络出版日期: 2018-08-15

基金资助

基于熵产理论的旋风分离器气固分离性能研究

Separation performance optimization of wave-plate mist eliminator based on response surface methodology

  • Weiwei MA Xiaolin WU Zhongli JI
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  • 1. College of Chemical Engineering, China University of Petroleum, Beijing 102249, China
    2. College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
    3. Beijing Key Laboratory of Process Fluid Filtration and Separation, Beijing 102249, China

Received date: 2017-10-18

  Revised date: 2018-01-15

  Online published: 2018-08-15

摘要

用响应面分析法分析不同排液结构对新式异型折流板除雾器气液分离性能的影响,并对排液结构参数进行优化设计. 通过单因素实验对比筛选对除雾器性能具有显著影响的关键参数,用中心复合设计实验建立响应面多元回归模型,分析影响除雾器性能系数的参数间交互作用,得出最优参数. 结果表明,影响除雾器性能参数的最优取值为分离气速2.6 m/s、排液钩高度7.3 mm、前置排液槽和后置排液槽宽度分别为3.1和2.3 mm. 优化的折流板除雾器性能系数计算值为2.073,实验值为1.875,优化结果较可靠.

本文引用格式

马巍威 吴小林 姬忠礼 . 基于响应面法的折流板除雾器分离性能优化[J]. 过程工程学报, 2018 , 18(4) : 689 -696 . DOI: 10.12034/j.issn.1009-606X.217369

Abstract

The influences of different drainage structures on the gas?liquid separation performance of wave-plate mist eliminator were analyzed and the parameters of drainage structure were optimized by response surface methodology. The single factor experiment was used to select the key parameters which had significant influence on the performance of the mist eliminator. The multivariate regression model was established using center compound design experiment in order to analyz the interaction of parameters which had influence on mist eliminator performance coefficient. The results showed that the key parameters which had significant influence on the performance of the mist eliminator and their values were separation gas velocity 2.6 m/s, height of drainage hook 7.3 mm, width of front-drainage pocket 3.1 mm and width of rear-drainage pocket 2.3 mm. The calculated value of mist eliminator performance coefficient was 2.073 while the test value was 1.875 which indicated that the optimization result of response surface methodology was credible.

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