When ultrasonic flowmeter is applied in wet gas measurement, the ultrasonic signal attenuate and fluctuate strongly because of liquid film and droplets in gas. It is hard to obtain the accurate time of flight of ultrasound. Besides, gas velocity distribution on pipe cross-section changes with different flow pattern, which is difficult to determine the measurement model. In order to solve these problems, a dual-channel ultrasonic flowmeter is specially designed and measurement system is built. Then, a dynamic threshold method based on statistical average signal amplitude is proposed to obtain time of flight of ultrasound in wet gas. Combined with the classical void fraction model, the wet gas velocity measurement model for the dual-channel ultrasonic flowmeter is established based on neural network. Finally, experiments are carried out on DN50 wet gas device, where pressure is 0.1MPa, gas superficial velocity is 5m/s-20m/s and liquid volume fraction is 0.2%-5%. The results show that the average relative error of gas velocity is 0.52% and the maximum relative uncertainty is 0.491%.
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