棒束通道气液两相流流型识别及动力学特性分析

采集棒束通道实验台上气液两相流4种流型压差信号,计算4种流型的多尺度边际谱熵,对其进行流型识别及动力学特性分析。实验结果表明:多尺度边际谱熵能从整体上区分4种流型,从频域细节尺度定量揭示不同流型间的动力学特性;利用多尺度边际谱熵增率和谱熵均值联合分布可定量准确区分4种流型,对泡状-搅混流这种难以区分的过渡流型也有较好效果;与支持向量机结合具有运算速度快、识别率高的优点,准确率高达98.11%,适合流型的在线识别。

Flow Pattern Identification and Dynamics Characteristics of Gas-liquid Two-phase Flow in Rod Bundle Channel

Four differential pressure signals of gas-liquid two-phase flow pattern in a rod bundle channel were collected and the multiple scale marginal spectrum entropies of four kinds of flow patterns were calculated, then the identification and dynamics characteristics of four kinds of flow patterns were analyzed.The experimental results show that multiple scale marginal spectrum entropy can distinguish four kinds of flow patterns from the whole, and the dynamics characteristics of different flow patterns can be revealed quantitatively from the detailed scale of frequency domain.The four kinds of flow patterns can be accurately distinguished by using multiple scale marginal spectrum entropy rate and spectral entropy mean joint distribution, and the bubbly and churn flow that it is difficult to distinguish such transitional flow also has a good effect.Combining with the support vector machine, the method has the advantages of fast operation and high recognition rate, its accuracy rate is up to 98.11%, and is suitable for online identification of flow patterns.