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Application of time–frequency entropy from wake oscillation to gas–liquid flow pattern identification

Journal of Central South University 2018年第7期25卷 1690-1700页

作者： HUANG Si-shi SUN Zhi-qiang ZHOU Tian ZHOU Jie-min School of Energy Science and Engineering Central South UniversityChangsha 410083China

Gas–liquid two-phase flow abounds in industrial processes and facilities. Identification of its flow pattern plays an essential role in the field of multiphase flow measurement. A bluff body was introduced in this study to recognize gas–liquid flow patterns by inducing fluid oscillation that enlarged differences between each flow pattern. Experiments with air–water mixtures were carried out in horizontal pipelines at ambient temperature and atmospheric pressure. Differential pressure signals from the bluff-body wake were obtained in bubble, bubble/plug transitional, plug, slug, and annular flows. Utilizing the adaptive ensemble empirical mode decomposition method and the Hilbert transform, the time–frequency entropy S of the differential pressure signals was obtained. By combining S and other flow parameters, such as the volumetric void fraction β, the dryness x, the ratio of density φ and the modified fluid coefficient ψ, a new flow pattern map was constructed which adopted S（1–x）φ and （1–β）ψ as the vertical and horizontal coordinates, respectively. The overall rate of classification of the map was verified to be 92.9% by the experimental data. It provides an effective and simple solution to the gas–liquid flow pattern identification problems.

关键词： gas–liquid two-phase flow wake oscillation flow pattern map time–frequency entropy ensemble empirical mode decomposition Hilbert transform

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