水平气液两相流流型图像信息递归特征分析

采用高速摄像机在气液两相流实验台上拍摄各种典型流型的流动时频，将单帧图像提取信息熵组成时间序列。对信息熵时间序列进行WVD分析，对气液两相流几种典型流型以及过渡流型的演化轨迹进行解析。同时对序列进行了近年来较少用到的非线性混沌递归图分析（RP），将其分析结果同WVD的分析结果进行对比，在对流型演化轨迹提出新的见解外也对WVD的分析结果进行验证。在分析后将100组不同流型的信息熵序列进行平均值计算，列出随气体体积流量增大的变化趋势图，进一步对流型信息熵与气流量的关系进行说明。最后讨论了气液两相流容积含气率与信息熵的关系。结果表明：流动图像的信息熵序列结合WVD与RP可以对气液两相流型演化轨迹进行很好表征。同时流型图像的信息熵能够对气液两相流各种流型的容积含气率进行表征，是一种有效的流型图像特征参数。

Recursive feature of gas-liquid two-phase flow pattern based on information entropy series of flow image

On the streaming video of all typical flow pattern filmings on the experiment system by the high-speed video camera，the information of a single-frame was extracted and made into time-series. The series was analyzed with the non-linear chaotic recurrence plot（RP），less used in the last years.It was combined with the average diagonal length and Shannon entropy of recursive features changed after the increase of gas superficial velocity.The results showed that the information entropy of flow image combined with RP could well characterize the evaluated tract of gas-liquid two-phase flow patterns.At the same time，the information well characterized the volume fraction of all kinds of gas-liquid two-phase flow patterns.The average diagonal length and recursive Shannon entropy of recursive features all increased first and then decreased with the increase of gas superficial velocity，and it reflected the transition of the mechanisms of five typical flow patterns from the recursive characteristics.