Abstract A method for analyzing the flow characteristics of gas-liquid two-phase flow in vertical pipelines based on time-frequency transformation and complex networks is proposed. This method is based on the measurement data collected by a digital electrical resistance tomography system. Three methods, Choi-Williams distribution (CWD), adaptive optimal kernel (AOK), and smooth pseudo Wigner-Ville distribution (SPWVD), are used to perform time frequency analysis on the pre-processed one-dimensional time series, and then extract energy sequences from the time frequency plane. The limited penetrable visibility graph method is used to construct complex networks for original time series and three types of energy series, respectively. Finally, three network indicators, namely, average clustering coefficient, average degree, and global efficiency, are used to characterize the evolution from bubbly flow to slug flow. The results show that the three network indicators of the complex network constructed from the original sequence are irregular; The average clustering coefficient and global efficiency corresponding to AOK and SPWVD are only regular under some operating conditions; The three network indicators corresponding to CWD all exhibit good regularity, which can more effectively reveal the complex flow behavior of gas-liquid two-phase flow.
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2024, Vol. 45 
