SCI和EI收录∣中国化工学会会刊

›› 2011, Vol. 19 ›› Issue (2): 243-252.

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Time-Frequency Signal Processing for Gas-Liquid Two Phase Flow Through a Horizontal Venturi Based on Adaptive Optimal-Kernel Theory

孙斌, 王二朋, 丁洋, 白宏震, 黄咏梅   

  1. College of Metrological Technology and Engineering, China Jiliang University, Hangzhou 310018, China
  • 收稿日期:2010-07-04 修回日期:2010-11-17 出版日期:2011-04-28 发布日期:2011-04-28
  • 通讯作者: SUN Bin,E-mail:bsun555@cjlu.edu.cn E-mail:bsun555@cjlu.edu.cn
  • 基金资助:
    Supported by the Natural Science Foundation of Zhejiang Province(Y1100842);the Planning Projects of General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China(2006QK23)

Time-Frequency Signal Processing for Gas-Liquid Two Phase Flow Through a Horizontal Venturi Based on Adaptive Optimal-Kernel Theory

SUN Bin, WANG Erpeng, DING Yang, BAI Hongzhen, HUANG Yongmei   

  1. College of Metrological Technology and Engineering, China Jiliang University, Hangzhou 310018, China
  • Received:2010-07-04 Revised:2010-11-17 Online:2011-04-28 Published:2011-04-28
  • Supported by:
    Supported by the Natural Science Foundation of Zhejiang Province(Y1100842);the Planning Projects of General Administration of Quality Supervision,Inspection and Quarantine of the People's Republic of China(2006QK23)

摘要: A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel (AOK) was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visually analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.

关键词: adaptive optimal-kernel, two-phase flow, time-frequency spectrum, time-frequency ridge, flow pattern identification

Abstract: A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel (AOK) was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visually analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.

Key words: adaptive optimal-kernel, two-phase flow, time-frequency spectrum, time-frequency ridge, flow pattern identification