气液两相流流型特性分析及其软件系统实现

发布时间：2018-05-30 08:07

本文选题：气液两相流 + 均方根　；参考：《青岛科技大学》2017年硕士论文

【摘要】：两相及多相流被称为“难测流体”。现在无论国内还是国外,都没有完美的两相流流型特性分析方法。但又因为它对工业生产有着极其重要的作用,所以近几年它一直是相关领域的学者们积极探索的课题。本文采用了多尺度能量特征方法进行气液两相流流型识别与分析,并且将等概率符号化样本熵(Equiprobable Symbolization Sample Entropy,ESSE)和模糊熵(Fuzzy Entropy,FuzzyEn)引入到两相流信号分析的领域,为两相流的动力学特性表征提供了一定的参考和思路。为了克服气液两相流流型信号的非线性和非平稳性的弊端,更加深入地揭示两相流流型信号的特性。我们采用了双树复小波分解方法,将气液两相流电导波动信号分解为7个尺度,提取多尺度的能量特征——均方根值(Root Mean Square,RMS),再对多尺度均方根值曲线进行线性拟合获得斜率,采用多尺度能量特征的方法进行气液两相流流型识别和两相流流型特性分析。基于等概率符号化样本熵、模糊熵的理论,对不同流型的动力学特性进行研究。通过对典型混沌信号和加噪信号的分析结果的讨论,验证了ESSE方法区分不同类型混沌信号的能力和抗噪能力。并且将模糊熵算法的两相流信号分析结果与传统样本熵(Sample Entropy,SE)和近似熵(Approximate Entropy,ApEn)算法的分析结果进行了对比研究。最后采用LabVIEW与MATLAB的混合编程,设计和实现了一个能够完成两相流数据获取、滤波和分析的LabVIEW软件系统。
[Abstract]:Two-phase and multi-phase flows are called "undetectable fluids". There is no perfect two-phase flow pattern analysis method both at home and abroad. However, because it plays an extremely important role in industrial production, it has been a topic actively explored by scholars in related fields in recent years. In this paper, the multi-scale energy characteristic method is used to identify and analyze the flow patterns of gas-liquid two-phase flow, and the equiprobability symbolized sample entropy (Equible Symbolization Sample EntropyEspe) and the fuzzy entropy fuzzy EntropyEnn (Fuzzy Entropy) are introduced into the field of two-phase flow signal analysis. It provides a certain reference and train of thought for the characterization of the kinetic characteristics of the two-phase flow. In order to overcome the nonlinearity and non-stationarity of the gas-liquid two-phase flow signal, the characteristics of the two-phase flow pattern signal are revealed more deeply. We use the double tree complex wavelet decomposition method to decompose the conductance wave signal of gas-liquid two-phase flow into seven scales, extract the multi-scale energy characteristic, root mean square root value (RMS), and then linear fit the multi-scale root mean square curve to obtain the slope. The multi-scale energy characteristic method is used to identify the gas-liquid two-phase flow pattern and analyze the two-phase flow pattern characteristics. Based on the theory of equal-probability symbolic sample entropy and fuzzy entropy, the dynamic characteristics of different flow patterns are studied. By discussing the analysis results of typical chaotic signals and noisy signals, the ability of ESSE method to distinguish different types of chaotic signals and to resist noise is verified. The results of two-phase flow signal analysis based on fuzzy entropy algorithm are compared with those of the traditional sample entropy method (sample EntropySe) and the approximate entropy approximation algorithm (ApEne). Finally, a LabVIEW software system which can acquire, filter and analyze two-phase flow data is designed and implemented by the mixed programming of LabVIEW and MATLAB.
【学位授予单位】：青岛科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O359.1

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