Image Processing of Gas-Liquid Two-Phase Flow in High-Speed Photography Based on Reconstruction Algorithm

As an increasingly popular flow metering technology, Coriolis mass flowmeter exhibits high measurement accuracy under single-phase flow condition and is widely used in the industry. However, under complex flow conditions, such as two-phase flow, the measurement accuracy is greatly decreased due to various factors including improper signal processing methods. In this study, three digital signal processing methods—the quadrature demodulation (QD) method, Hilbert method, and sliding discrete time Fourier transform method—are analyzed for their applications in processing sensor signals and providing measurement results under gas-liquid two-phase flow condition. Based on the analysis, specific improvements are applied to each method to deal with the signals under two-phase flow condition. For simulation, sensor signals under single- and two-phase flow conditions are established using a random walk model. The phase difference tracking performances of these three methods are evaluated in the simulation. Based on the digital signal processor, a converter program is implemented on its evaluation board. The converter program is tested under single- and two-phase flow conditions. The improved signal processing methods are evaluated in terms of the measurement accuracy and complexity. The QD algorithm has the best performance under the single-phase flow condition. Under the two-phase flow condition, the QD algorithm performs a little better in terms of the indication error and repeatability than the improved Hilbert algorithm at 160, 250, and 420 kg/h flow points, whereas the Hilbert algorithm outperforms the QD algorithm at the 600 kg/h flow point.

Chunhui Li

Papers

Improvement of signal processing in Coriolis mass flowmeters for gas-liquid two-phase flow