TY - JOUR
T1 - Flowrate Measurement of Gas–Liquid Two-Phase Flow Using a Throat-Extended Venturi Tube and a Microwave Resonant Cavity
AU - Suo, Peng
AU - Sun, Jiangtao
AU - Sun, Shijie
AU - Xu, Ying
AU - Gao, Zhongke
AU - Lu, Fanghao
AU - Xu, Hao
AU - Xu, Lijun
AU - Yan, Yong
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - This article presents a novel method for flowrate measurement of gas–liquid two-phase flow using a throat-extended Venturi tube (TEVT) combined with a microwave resonant cavity (MRC). First, a total flowrate model is developed from differential pressure (DP) equations across the convergent and straight sections of the TEVT. Subsequently, a gas–liquid flowrate ratio model is established using microwave resonant frequency and multiple DP fluctuations, fit via support vector machine (SVM). The particle swarm optimization (PSO) algorithm then solves the coupled equations for gas and liquid flowrates. The proposed method integrates two sensing modalities and leverages static and dynamic features of raw measurement data to achieve simultaneous gas–liquid flowrate prediction. Experiments were conducted on a gas–liquid two-phase flow test facility using the TEVT and MRC. Within gas flowrate of 0.07–8.09 m3/h and liquid flowrate of 1.12–13.64 m3/h, the relative errors of the predicted liquid and gas flowrates are within ±5% and ±9.5%, respectively. The results demonstrate that the proposed method performs well in predicting gas–liquid two-phase flowrate, offering potential for extension to broader range of flow conditions.
AB - This article presents a novel method for flowrate measurement of gas–liquid two-phase flow using a throat-extended Venturi tube (TEVT) combined with a microwave resonant cavity (MRC). First, a total flowrate model is developed from differential pressure (DP) equations across the convergent and straight sections of the TEVT. Subsequently, a gas–liquid flowrate ratio model is established using microwave resonant frequency and multiple DP fluctuations, fit via support vector machine (SVM). The particle swarm optimization (PSO) algorithm then solves the coupled equations for gas and liquid flowrates. The proposed method integrates two sensing modalities and leverages static and dynamic features of raw measurement data to achieve simultaneous gas–liquid flowrate prediction. Experiments were conducted on a gas–liquid two-phase flow test facility using the TEVT and MRC. Within gas flowrate of 0.07–8.09 m3/h and liquid flowrate of 1.12–13.64 m3/h, the relative errors of the predicted liquid and gas flowrates are within ±5% and ±9.5%, respectively. The results demonstrate that the proposed method performs well in predicting gas–liquid two-phase flowrate, offering potential for extension to broader range of flow conditions.
KW - Flowrate measurement
KW - gas–liquid two-phase flow
KW - microwave resonant cavity (MRC)
KW - optimization solution
KW - throat-extended Venturi tube (TEVT)
UR - https://www.scopus.com/pages/publications/105018521728
U2 - 10.1109/TIM.2025.3614895
DO - 10.1109/TIM.2025.3614895
M3 - 文章
AN - SCOPUS:105018521728
SN - 0018-9456
VL - 74
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 9537209
ER -