Comparative Analysis Of Pressure Signals And Pressure Difference Signals Of The Two-phase Flow Based On Spectrum Transformation

The phenomenon of two-phase flow occurs widely in nature and many industrial processes. The distribution of the two-phase flow medium, namely flow pattern, greatly influences the properties of the two-phase flow such as the pressure loss, the conductivity, the ability of mass transfer and so on. Meanwhile, it also affects the accurate measurement of the flow parameters and the operating characteristic of the flow system. The study of the flow pattern detection of the gas-liquid two-phase flow not only has much practical value and academic value, but also provides forceful technical support for the safety of relevant industrial equipment and the economy of the design and the operation. Therefore, the study of the flow pattern detection is always an important subject in the field of gas-liquid two-phase flow.Nowadays, the gas-liquid two-phase flow pattern detection system is relatively mature and widely used in many cases from Hurst index calculation of the pressure signals of the gas-liquid two-phase flow pattern to the application of EMD neural networks, from the application of HHT to the application of image processing techniques. The pressure signal of the gas-liquid two-phase flow pattern is an integrated carrier of all kinds of information, which contains a lot of characteristic parameters reflecting the flow pattern. The pressure wave is a wave process in which the tiny disturbance happening in some area of the fluid is transmitted to other areas. Its existence accelerates the flow of fluid, increases the transmission of energy and momentum among interfaces and greatly changes the properties of heat transfer, mass transfer and resistance of the two-phase flow.In this paper, experimental studies are implemented on the laboratory bench of the gas-liquid two-phase flow and a comparative analysis between the pressure signals and the pressure difference wave signals of the air-water two-phase flow of the horizontal tube obtained is made as follows: Firstly, the PSD, AR, BT power spectra and WVD transformation of the two kinds of signals are made and the four characteristic parameters of PSD combined with RBF neural networks are used for flow pattern detection; Secondly, the pressure signals and the pressure difference signals transformed are comparatively analyzed from three aspects namely energy, power and average value; Thirdly, the pressure signals and the pressure difference signals are transformed and compared based on high-order power spectrum namely bi-spectrum, which provides a new tentative theory for flow characteristics and flow pattern detection.