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Analysis of chaos characteristics of gas-liquid two-phase flow noise

机译：气液两相流噪声混沌特性分析

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The noise signals of gas-liquid two-phase flow contain abundant information, which can reflect the change of gas liquid two phase flow rate, phase holdup and flow rate and so on. In this paper, acoustic emission technology is used to quantitatively measure the noise of gas-liquid two-phase flow, and the flow noise signal is analyzed by using chaotic information processing technology. The delay time was determined though compared the four methods, the average displacement method, autocorrelation method, mutual information method and C-C algorithm, finally, C-C algorithm was selected. Compared with four kinds of embedding dimension methods: the FNN method, Cao's algorithm, G-P algorithm, and C-C algorithm, The G-P algorithm is adopted to calculate the embedding dimension of phase space reconstruction. The attractor is reconstructed using polar coordinate space. At the same time, five parameters of correlation dimension, K-entropy, Hurst exponent, mobility and complexity are applied to quantitatively analyze chaotic attractors. The analysis shows that the polar coordinates clearly indicate the amplitude and phase signals of the gas and liquid phases acquired by the acoustic emission system in the gas-liquid two-phase flow; From the five characteristic parameters, it can be seen that when the flow pattern changes, the mobility increases instantly by 76.92%. With the increase of the gas volume, the mobility growth rate increases from 12.43% to 62.01% under the same flow pattern. The complexity has decreased by 33.65%. When there is a large amount of traffic, it will reduce the correlation dimension to 96.61%, and the K-entropy will decrease to 97.53%. The chaotic characteristics describe the variation of gas-liquid two-phase flow, which provides another idea for the flow-type transformation.
机译：气液两相流的噪声信号包含丰富的信息，这可以反映气体液体的变化两相流速，相位保持和流速等。在本文中，使用声发射技术来定量测量气液两相流的噪声，通过使用混沌信息处理技术分析流噪声信号。确定了延迟时间，但比较了四种方法，平均位移方法，自相关方法，相互信息方法和C-C算法，最后，选择了C-C算法。与四种嵌入尺寸方法相比：FNN方法，CAO的算法，G-P算法和C-C算法，采用G-P算法计算相空间重建的嵌入尺寸。使用极性坐标空间重建吸引子。同时，应用了五个相关维，k熵，赫斯特指数，移动性和复杂性的参数，以定量分析混沌吸引子。该分析表明，极性坐标清楚地表明了气液两相流中的声发射系统获取的气体和液相的幅度和相位信号;从五个特征参数来看，可以看出，当流动模式发生变化时，迁移率立即增加76.92％。随着气体体积的增加，迁移率生长速率在相同的流动模式下从12.43％增加到62.01％。复杂性降低了33.65％。当有大量的流量时，将相关尺寸降低至96.61％，k熵将减少到97.53％。混沌特性描述了气液两相流的变化，为流动型变换提供了另一种思想。

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