中文摘要：

为了考察从时间序列提取的复杂性测度与气液两相流流型变化之间的关系，本文首先讨论了三种复杂性测度（Lempel-Ziv复杂性、功率谱熵和近似熵）对周期信号、随机信号、混合随机信号和混沌信号的识别能力，然后分析了时间序列长度对复杂性计算的影响．在此基础上，从实际测量的80种垂直上升管中气液两相流电导波动信号中提取了这三种复杂性测度，结果表明：三种复杂度对两相流流型变化是敏感的，通过对三种复杂度随两相流流动参数变化规律分析，可以得到气液两相流动力学结构反演特征，为揭示气液两相流流型转化机理提供了一种有效的辅助诊断工具．

英文摘要：

To discuss the relation between complexity measures extracted from time series and flow pattern transition in gas-liquid twophase flow, this paper analyzes the recognition capability of three complexity measures, including Lempel-Ziv complexity, spectral entropy and approximate entropy to different signals, such as periodic signal, stochastic signal, mixed stochastic signal and chaotic signal, and then the paper discusses the influence of the length of time series to the algorithms of the three complexity measures. Based on the above studies, we extracted the three complexity measures from eighty conductance fluctuating signals of gas-liquid two phase flow in vertical upward pipe. The results indicate that the three complexity measures are sensitive to the flow pattern transition in gas-liquid two-phase flow. By analyzing the rules of three complexity measures with the changes of gas-liquid two-phase flow parameters, we can get the dynamics structure inversion characters of gas-liquid two-phase flow, and they provide an efficient, supplementary diagnostic tool to reveal the flow pattern transition mechanism of gas-liquid two-phase flow.