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Classification of gas-liquid flow patterns by the norm entropy of wavelet decomposed pressure fluctuations across a bluff body

机译:利用小波分解虚张声势上的压力波动的范数熵对气液流型进行分类

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摘要

Identification of gas-liquid flow patterns remains one of the paramount needs in multiphase flow metering. It is hardly possible to realize accurate measurement and control of parameters in a gas-liquid flow system without a clear understanding of its flow pattern. Here we explore the characterization of gas-liquid flow patterns using the norm entropy extracted from the wavelet decomposed pressure fluctuations across a bluff body. Experiments on air-water two-phase flow at ambient temperature and atmospheric pressure are carried out in the bubble, plug, slug and annular flow patterns. On the basis of the experimental results, two original flow-pattern maps are constructed: one is coordinated with the average norm entropy versus the total mass flow rate, and the other is the average norm entropy versus the volumetric void fraction. Verification tests demonstrate that the overall identification rates of the flow-pattern maps developed exceed 95%. This approach provides an effective and simple solution to the classification of gas-liquid flow patterns.
机译:气液流型态的识别仍然是多相流量计量中最重要的需求之一。在没有清楚了解其流动方式的情况下,几乎不可能在气液流动系统中实现对参数的精确测量和控制。在这里,我们使用从小波分解的虚张声势上的压力波动中提取的范数熵来探索气液流动模式的特征。在气泡,旋塞,团状和环形流动模式下,在环境温度和大气压下进行了空气-水两相流动的实验。根据实验结果,构建了两个原始的流型图:一个与平均范数熵对总质量流率相协调,另一个与平均范数熵对体积空隙率相对应。验证测试表明,开发的流模式图的总体识别率超过95%。这种方法为气液流动模式的分类提供了有效而简单的解决方案。

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