Gas ultrasonic flowmeter measurement method based on cross-segmented differential evolution support vector regression
In order to further improve the measurement accuracy of the full-range gas ultrasonic flowmeter,based on multi-path acoustic arrival time and real-time temperature,a cross-segmented differential evolution support vector regression(DE-SVR)model is proposed.Considering that the gas is in different fluid states under different flow rates,a cross-segmented processing method is proposed,and the SVR parameters are optimized using the DE algorithm.The results show that for the full range of 16-1600 m3/h,the mean relative errors of the cross-segmented DE-SVR and the traditional integration method in calculating the gas flow rate are 0.00447 and 0.02781,respectively,and the former is 83.93％lower than the latter.For a small flow rate of 16-160 m3/h,the mean relative errors calculated by the cross-segmented DE-SVR and the unsegmented DE-SVR algorithms are 0.00436 and 0.03214,respectively,and the former is 86.43％lower than the latter.The method effectively avoids the influence of uncertainties in parameters such as acoustic channel length,probe angle and pipe diameter on the flow calculation,and provides high accuracy measurement of the full range of gas flow.
Gas ultrasonic flowmeterSupport vector regressionDifferential evolutionMachine learning
万方数据
维普
