Dynamic signal analysis for gas-oil two-phase flow in time-frequency domain based on electrical capacitance tomography
In this research,based on virtual ECT sensors and flow-electric coupling simulation method,four typical oil gas two-phase flow patterns and their corresponding measurement signals were dynamically simulated.Time-series signals of pressure and capacitance were analyzed by applying multi-resolution analysis(MRA)and time-frequency analysis methods based on wavelet transform.Continuous wavelet transform can display the energy distribution in the time-frequency two-dimensional domain and effectively locate flow fluctuations.Based on the wavelet MRA method,the original signals were decomposed into different frequency bands within the same time range.As results,both pressure and capacitance signal analyses showed the similar migration pattern of main frequency banded from middle to low and then to high frequency with flow pattern changes,which provided flow pattern identification with a potential criterion.This method was validated through experimental measurements in the intermittent flow,effectively reflecting the changes in slug frequency,flow fluctuation,and liquid slug morphology under different flow rates.The research method and results in this paper are expected to provide reliable means for flow pattern identification and process monitoring in practical industrial processes.
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