Analysis of total energy and time-frequency entropy of gas-liquid two-phase flow pattern
Analysis of total energy and time-frequency entropy of gas-liquid two-phase flow pattern
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气液两相流型态总能量及时频熵分析
DOI：
10.1016/j.ces.2012.07.028
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发表时间：
2012-09-12
影响因子：
4.7
通讯作者：
Sun, Bin
中科院分区：
文献类型：
--
作者：
Du, Meng;Jin, Ning-De;Sun, Bin
本文首先对Wigner-Ville分布、Choi-Williams分布和自适应最优核时频表示（AOK TFR）三种时频表示算法进行了仿真研究。结果表明，AOK TFR可以抑制交叉项，同时保持较高的时频浓度。在这方面，我们使用AOK TFR分析垂直向上气液两相流实验中测量到的波动信号。此外，我们从AOK TFR中提取总能量和时频熵来表征不同流动模式下的动态行为。研究发现，总能量和熵对流型演变非常敏感，总能量和熵的联合分布不仅可以作为区分不同流型的有力工具，而且可以揭示气液流型背后复杂的动力学行为。(C) 2012 Elsevier Ltd.版权所有。
In this paper, we first make a simulation investigation to evaluate three time-frequency representation algorithms, i.e., Wigner-Ville distribution, Choi-Williams distribution and adaptive optimal kernel time-frequency representation (AOK TFR). The results indicate that AOK TFR can suppress the cross-term while keeping a high time-frequency concentration. In this regard, we use AOK TFR to analyze the fluctuating signals measured from vertical upward gas-liquid two-phase flow experiments. Moreover, we extract total energy and time-frequency entropy from the AOK TFR to characterize dynamic behaviors underlying different flow patterns. We find the total energy and entropy are sensitive to the flow pattern evolutions and the joint distribution of total energy and entropy can be a powerful tool for not only distinguishing different flow patterns but also revealing complex dynamic behaviors underlying gas-liquid flow patterns. (C) 2012 Elsevier Ltd. All rights reserved.