Gas-liquid flows abound in a great variety of industrial processes. Correct recognition of the regimes of a gasliquid flow is one of the most formidable challenges in multiphase flow measurement. Here we put forward a novel approach to the classification of gas-liquid flow patterns. In this method a flow-pattern map is constructed based on the average energy of intrinsic mode function and the volumetric void fraction of gas-liquid mixture. The intrinsic mode function is extracted from the pressure fluctuation across a bluff body using the empirical mode decomposition technique. Experiments adopting air and water as the working fluids are conducted in the bubble, plug, slug, and annular flow patterns at ambient temperature and atmospheric pressure. Verification tests indicate that the identification rate of the flow-pattern map developed exceeds 90%. This approach is appropriate for the gas-liquid flow pattern identification in practical applications.
To find effective and practical methods to distinguish gas-liquid two-phase flow patterns, new flow pattern maps are established using the differential pressure through a classical Venturi tube. The differential pressure signal was first decomposed adaptively into a series of intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition. Hilbert marginal spectra of the IMFs showed that the flow patterns are related to the amplitude of the pressure fluctuation. The cross-correlation method was employed to sift the characteristic IMF, and then the energy ratio of the characteristic IMF to the raw signal was proposed to construct flow pattern maps with the volumetric void fraction and with the two-phase Reynolds number, respectively. The identification rates of these two maps are verified to be 91.18% and 92.65%. This approach provides a cost-effective solution to the difficult problem of identifying gas-liquid flow patterns in the industrial field.