| 基于随机子空间结合稳定图的气液两相流型分析 |
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| 引用本文： | 李洪伟,周云龙,刘旭,孙斌.基于随机子空间结合稳定图的气液两相流型分析[J].物理学报,2012,61(3):30508-030508. |
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| 作者姓名： | 李洪伟 周云龙 刘旭 孙斌 |
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| 作者单位： | 东北电力大学能源与动力工程学院,吉林,132012 |
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| 基金项目： | 国家自然科学基金(批准号: 50976018) 和吉林省自然科学基金(批准号: 20101562) 资助的课题. |
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| 摘 要： | 研究了几种典型气液两相流流型的稳定图特征,并应用随机子空间方法对47种流动条件下的流型 信号进行了识别.研究结果表明:稳定图特征能够反映出复杂时间序列的内部特征,利用其提取的直线度特征 值可以对时间序列的特征进行量化分析,三种典型流型的稳定图特征差异较明显,泡状流的稳定图特征最为 混乱,雾状流次之,段塞流最为规整.应用随机子空间方法对气液两相流图像灰度波动序列进行特征向量提取 和辨识,通过幅值以及相角的分布特征能够对不同工况下的流型样本进行准确分类,为多相流的分类提供了 一条新路径.同时基于稳定图的分析方法为进一步揭示多相流的流动机理提供有益的探索.
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| 关 键 词： | 随机子空间 稳定图 气液两相流 动力学特性 |
| 收稿时间： | 2011-05-16 |
| 修稿时间： | 6/2/2011 12:00:00 AM |
Stochastic subspsace parameter identification and stability diagram of gas-liquid two-phase flow patterns |
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| Li Hong-Wei,Zhou Yun-Long,Liu Xu and Sun Bin.Stochastic subspsace parameter identification and stability diagram of gas-liquid two-phase flow patterns[J].Acta Physica Sinica,2012,61(3):30508-030508. |
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| Authors: | Li Hong-Wei Zhou Yun-Long Liu Xu and Sun Bin |
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| Institution: | College of Energy Resource and Mechanical Engineering, Northeast Dianli University, Jilin 132012, China;College of Energy Resource and Mechanical Engineering, Northeast Dianli University, Jilin 132012, China;College of Energy Resource and Mechanical Engineering, Northeast Dianli University, Jilin 132012, China;College of Energy Resource and Mechanical Engineering, Northeast Dianli University, Jilin 132012, China |
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| Abstract: | The characteristics of stability diagram of several typical flow patterns are studied, and the signals of flow patterns under 47 kinds of flowing conditions are identified with stochastic subspace parameter identification. The results show that the characteristic of a stability diagram can reflect the internal characteristics of complex time series, the characteristics of time series can be quantified by extracted straightness characteristics and the differences of characteristics of stability diagrams of three typical flow patterns. The characteristics of stability diagrams of bubble flow are the most confused and followed by Mist flows'. Slug flows' are the most regular. The extraction and recognition for characteristics of gray fluctuation sequence of gas-liquid two-phase images and the accurate classification for flow pattern samples provide a new path for the classification of multi-phase flow patterns. At the same time, the stability diagram analysis method provides a useful exploration for the further revelation of flowing mechanism of multi-phase flows. |
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| Keywords: | stochastic subspsace parameter identification stability diagram gas-liquid two-phase flow dynamic characteristic |
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