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Arif MZ, Seppänen A, Kolehmainen V, Vauhkonen M. Dual-Modal Electrical Imaging of Two-Phase Flow-Experimental Evaluation of the State Estimation Approach. Sensors (Basel) 2023; 23:s23094462. [PMID: 37177666 PMCID: PMC10181751 DOI: 10.3390/s23094462] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/21/2023] [Accepted: 04/28/2023] [Indexed: 05/15/2023]
Abstract
Accurate measurement of two-phase flow quantities is essential for managing production in many industries. However, the inherent complexity of two-phase flow often makes estimating these quantities difficult, necessitating the development of reliable techniques for quantifying two-phase flow. In this paper, we investigated the feasibility of using state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flow. We utilized electromagnetic flow tomography (EMFT) to estimate velocity fields and electrical tomography (ET) to determine phase fraction distributions. In state estimation, the contribution of the velocity field to the temporal evolution of the phase fraction distribution was accounted for by approximating the process with a convection-diffusion model. The extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) were used to reconstruct the temporally evolving velocity and phase fraction distributions, which were further used to estimate the volumetric flow rates of the phases. Experimental results on a laboratory setup showed that the FIKS approach outperformed the conventional stationary reconstructions, with the average relative errors of the volumetric flow rates of oil and water being less than 4%. The FIKS approach also provided feasible uncertainty estimates for the velocity, phase fraction, and volumetric flow rate of the phases, enhancing the reliability of the state estimation approach.
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Affiliation(s)
- M Ziaul Arif
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
- Department of Mathematics, University of Jember, Jember 68121, Indonesia
| | - Aku Seppänen
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Ville Kolehmainen
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Marko Vauhkonen
- Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland
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Jang GG, Kasturi A, Stamberga D, Custelcean R, Keum JK, Yiacoumi S, Tsouris C. Ultra-fast Microwave Regeneration of CO2 Solid Sorbents for Energy-Efficient Direct Air Capture. Sep Purif Technol 2022. [DOI: 10.1016/j.seppur.2022.123053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Hlava J, Abouelazayem S. Control Systems with Tomographic Sensors-A Review. Sensors (Basel) 2022; 22:s22082847. [PMID: 35458833 PMCID: PMC9032538 DOI: 10.3390/s22082847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/24/2022] [Accepted: 04/04/2022] [Indexed: 02/04/2023]
Abstract
Industrial process tomography offers two key advantages over conventional sensing systems. Firstly, process tomography systems provide information about 2D or 3D distributions of the variables of interest. Secondly, tomography looks inside the processes without penetrating them physically, i.e., sensing is possible despite harsh process conditions, and the operation of the process is not disturbed by intrusive sensors. These advantages open new perspectives for the field of process control, and the potential of closed-loop control applications is one of the main driving forces behind the development of industrial tomography. Despite these advantages and decades of development, closed-loop control applications of tomography are still not really common. This article provides an overview of the current state-of-the-art in the field of control systems with tomographic sensors. An attempt is made to classify the different control approaches, critically assess their strengths and weak points, and outline which directions may lead to increased future utilization of industrial tomography in the closed-loop feedback control.
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Hampel U, Babout L, Banasiak R, Schleicher E, Soleimani M, Wondrak T, Vauhkonen M, Lähivaara T, Tan C, Hoyle B, Penn A. A Review on Fast Tomographic Imaging Techniques and Their Potential Application in Industrial Process Control. Sensors (Basel) 2022; 22:s22062309. [PMID: 35336477 PMCID: PMC8948778 DOI: 10.3390/s22062309] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/27/2022] [Accepted: 03/07/2022] [Indexed: 02/04/2023]
Abstract
With the ongoing digitalization of industry, imaging sensors are becoming increasingly important for industrial process control. In addition to direct imaging techniques such as those provided by video or infrared cameras, tomographic sensors are of interest in the process industry where harsh process conditions and opaque fluids require non-intrusive and non-optical sensing techniques. Because most tomographic sensors rely on complex and often time-multiplexed excitation and measurement schemes and require computationally intensive image reconstruction, their application in the control of highly dynamic processes is often hindered. This article provides an overview of the current state of the art in fast process tomography and its potential for use in industry.
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Affiliation(s)
- Uwe Hampel
- Institute of Fluid Dynamics, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany; (E.S.); (T.W.)
- Institute of Power Engineering, Technische Universität Dresden, 01062 Dresden, Germany
- Correspondence:
| | - Laurent Babout
- Institute of Applied Computer Science, Lodz University of Technology, Stefanowski 18, 90-937 Lodz, Poland; (L.B.); (R.B.)
| | - Robert Banasiak
- Institute of Applied Computer Science, Lodz University of Technology, Stefanowski 18, 90-937 Lodz, Poland; (L.B.); (R.B.)
| | - Eckhard Schleicher
- Institute of Fluid Dynamics, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany; (E.S.); (T.W.)
| | - Manuchehr Soleimani
- Engineering Tomography Lab (ETL), Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK;
| | - Thomas Wondrak
- Institute of Fluid Dynamics, Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany; (E.S.); (T.W.)
| | - Marko Vauhkonen
- Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland; (M.V.); (T.L.)
| | - Timo Lähivaara
- Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland; (M.V.); (T.L.)
| | - Chao Tan
- Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China;
| | - Brian Hoyle
- School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK;
| | - Alexander Penn
- Institute of Process Imaging, Hamburg University of Technology, Denickestraße 17, 21073 Hamburg, Germany;
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Sattar MA, Garcia MM, Portela LM, Babout L. A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows. Sensors (Basel) 2022; 22:1834. [PMID: 35270982 DOI: 10.3390/s22051834] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/21/2022] [Accepted: 02/23/2022] [Indexed: 01/27/2023]
Abstract
Electrical resistance tomography (ERT) has been used in the literature to monitor the gas–liquid separation. However, the image reconstruction algorithms used in the studies take a considerable amount of time to generate the tomograms, which is far above the time scales of the flow inside the inline separator and, as a consequence, the technique is not fast enough to capture all the relevant dynamics of the process, vital for control applications. This article proposes a new strategy based on the physics behind the measurement and simple logics to monitor the separation with a high temporal resolution by minimizing both the amount of data and the calculations required to reconstruct one frame of the flow. To demonstrate its potential, the electronics of an ERT system are used together with a high-speed camera to measure the flow inside an inline swirl separator. For the 16-electrode system used in this study, only 12 measurements are required to reconstruct the whole flow distribution with the proposed algorithm, 10× less than the minimum number of measurements of ERT (120). In terms of computational effort, the technique was shown to be 1000× faster than solving the inverse problem non-iteratively via the Gauss–Newton approach, one of the computationally cheapest techniques available. Therefore, this novel algorithm has the potential to achieve measurement speeds in the order of 104 times the ERT speed in the context of inline swirl separation, pointing to flow measurements at around 10kHz while keeping the average estimation error below 6 mm in the worst-case scenario.
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