Abstract Differential pressure of gas-liquid mixture contains abundant information about fluid flow and its nature. In this paper, a differential pressure across a Venturi tube is measured for a gas-liquid mixture. Trend component and fluctuation components of the differential pressure are extracted using Extreme-Point Symmetric Mode Decomposition. The analysis shows that the mean of the trend component is related to liquid flowrate, and the amplitude of the fluctuation components is correlated to voidage and flow pattern. Hence, a fluctuation coefficient based approach to access voidage is proposed. This is based on the trend and fluctuation components. Since there exists an influence of gas/liquid flowrate, fluid density and voidage on fluctuation coefficient, their qualitative relationships are analyzed to find the appropriate variables to modify the fluctuation coefficient. Experimental data are used to determine the appropriate specific modification parameters. The modified fluctuation coefficient is found to be flow pattern dependent, and hence fuzzy pattern recognition is adopted to identify flow patterns combining statistics from differential pressure. Finally, a flow pattern-based correlation is proposed to estimate the voidage. Verifications through confrontation with experimental results show that the proposed correlation is effective in estimating voidage of mixtures.

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一种基于压差波动的气液混合物空隙率关联新方法

摘要 气液混合物压差包含了大量关于流体流动及其性质的信息。在本文中，测量了气液混合物穿过文丘里管的压差。使用极值点对称模式分解提取压差的趋势分量和波动分量。分析表明，趋势分量的均值与液体流量有关，波动分量的幅值与空隙率和流型有关。因此，提出了一种基于波动系数的通路空隙率方法。这是基于趋势和波动组件。由于存在气/液流量、流体密度和空隙率对波动系数的影响，分析它们的定性关系以找到合适的变量来修改波动系数。实验数据用于确定适当的特定改性参数。发现修正的波动系数与流型相关，因此采用模糊模式识别来结合压差统计来识别流型。最后，提出了一种基于流动模式的相关性来估计空隙率。通过与实验结果的对比验证表明，所提出的相关性在估计混合物的空隙率方面是有效的。因此采用模糊模式识别来结合压差统计来识别流动模式。最后，提出了一种基于流动模式的相关性来估计空隙率。通过与实验结果的对比验证表明，所提出的相关性在估计混合物的空隙率方面是有效的。因此采用模糊模式识别来结合压差统计来识别流动模式。最后，提出了一种基于流动模式的相关性来估计空隙率。通过与实验结果的对比验证表明，所提出的相关性在估计混合物的空隙率方面是有效的。