The paper presents experimental investigations of pressure fluctuations near the tip clearance region of the rotor blades of the axial-flow low-speed compressor stage in stable and unstable parts of the overall performance characteristic. In this investigation, unsteady pressure was measured with the use of high frequency pressure transducers mounted on the casing wall of rotor passage. The pressure signals and their frequency characteristics were analyzed during the steady-state processes, before the rotating stall, during the transition from the steady-state process to the rotating stall, and during a stabilized phenomenon of low-frequency rotating stall. As the operating point moves to the unstable region of flow characteristic, an inception of the rotating stall can be observed, which rotates with a speed of about 41.4% of the rotor speed. The results of this study confirm that in the low-speed axial compressor stage operating in a rotating stall regime there appears one stall cell that spreads over to adjacent rotor blade channels. As the flow rate is reduced further, the frequency of the rotating stall decreased to 34.8% of the rotor speed and the number of blade channels with the stall cell increases.

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.