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Dual-Modal Electrical Imaging of Two-Phase Flow-Experimental Evaluation of the State Estimation Approach
M Ziaul Arif1,2, Aku Seppänen1, Ville Kolehmainen1
1Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland.
Sensors (Basel, Switzerland)
|May 13, 2023
Summary
This study introduces state estimation for dynamic image reconstruction in dual-modal tomography, improving two-phase flow measurements. The fixed-interval Kalman smoother achieved less than 4% error in oil-water flow rate estimation.
Area of Science:
- Fluid dynamics
- Tomographic imaging
- State estimation
Background:
- Accurate two-phase flow measurement is crucial for industrial production management.
- The complexity of two-phase flow poses challenges for accurate quantity estimation.
- Development of reliable quantification techniques is essential.
Purpose of the Study:
- Investigate state estimation for dynamic image reconstruction in dual-modal tomography.
- Apply to two-phase oil-water flow.
- Enhance accuracy and reliability of flow measurements.
Main Methods:
- Utilized electromagnetic flow tomography (EMFT) for velocity field estimation.
- Employed electrical tomography (ET) for phase fraction distribution determination.
- Applied extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) with a convection-diffusion model for dynamic reconstruction.
Main Results:
- FIKS approach outperformed conventional stationary reconstructions.
- Achieved average relative errors below 4% for oil and water volumetric flow rates.
- FIKS provided feasible uncertainty estimates for key flow parameters.
Conclusions:
- State estimation, particularly FIKS, is a feasible and reliable method for dynamic image reconstruction in dual-modal tomography.
- The approach significantly improves the accuracy of two-phase oil-water flow rate estimation.
- The method enhances the overall reliability of flow measurement systems.
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