Measurement of void fraction in gas-water bubbly flow using a derived multi-eigenvalue sequence from normalized EIT impedance matrix

Abstract

Void fraction is one of the dominant parameters of gas-water two-phase flow. Its accurate measurement plays an important role in achieving parameter control and reliable operation in industrial processes. This article proposes a more practical method for the measurement of void fraction in gas-water bubbly flow using a derived multi-eigenvalue sequence from a normalized electrical impedance tomography impedance matrix. The relations between eigenvalues and void fraction, bubble radius, number of bubbles are investigated by numerical simulations, which illustrates the superiority of using multi-eigenvalue rather than the largest eigenvalue for void fraction prediction. The nonlinear mapping between the multi-eigenvalue sequence and void fraction is established by applying the XGBoost model with a sliding window of time series. This proposed method is verified by static and dynamic experiments using a self-developed setup in our laboratory, generating stable gas-water bubbly flow with void fraction of less than 0.12. It is shown that the proposed method can predict void fraction with a relative deviation of 10%. Compared with the conventional method based on the largest eigenvalue, the proposed method efficiently improves the measurement accuracy of void fraction in gas-water bubbly flow and applicability in actual measurement of two-phase flow, which can be further extended to other flow regimes.