Analysis of chaos characteristics of gas-liquid two-phase flow noise. (March 2019)

• Record Type: Journal Article
• Authors: Fang, Lide; Zeng, Qiaoqiao; Faraj, Yousef; Zhao, Ning; Wei, Zihui; Li, Xiaoting
• Is Part Of: Flow measurement and instrumentation. Volume 65(2019)
• Page Start: 98
• Page End: 109
• Publication Date: 2019-03
• Subjects: Chaos -- Phase space reconstruction -- Polar coordinates -- Mobility -- Complexity; Fluid dynamic measurements -- Periodicals; Flow meters -- Periodicals; Fluides, Dynamique des -- Mesure -- Périodiques; Débitmètres -- Périodiques; 681.2805
• DOI: 10.1016/j.flowmeasinst.2018.11.008
• Languages: English
• ISSNs: 0955-5986

Abstract

Abstract: 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. Highlights: Comparing average displacement method, autocorrelation function method, mutual information, and C-C algorithm, C-C algorithm is used as the algorithm of delay time. Comparing FNN, G-P algorithm and C-C algorithm, the algorithm to determine the optimal embedding dimension is the G-P algorithm. After the phase space reconstruction is implemented, the amplitude and phase in the polar coordinates are used to more clearly distinguish the sound signal. Using the correlation dimension, K-entropy, Hurst exponent, mobility and complexity as the five characteristic parameters to describe the variation of gas-liquid two-phase flow.