A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows
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...
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MDPI AG
2022-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/5/1834 |
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| author | Muhammad Awais Sattar Matheus Martinez Garcia Luis M. Portela Laurent Babout |
| author_facet | Muhammad Awais Sattar Matheus Martinez Garcia Luis M. Portela Laurent Babout |
| author_sort | Muhammad Awais Sattar |
| collection | DOAJ |
| description | 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 10<sup>4</sup> 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. |
| first_indexed | 2024-03-09T20:21:12Z |
| format | Article |
| id | doaj.art-41359de283f1470f882fe09b1cde78f2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T20:21:12Z |
| publishDate | 2022-02-01 |
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| spelling | doaj.art-41359de283f1470f882fe09b1cde78f22023-11-23T23:46:58ZengMDPI AGSensors1424-82202022-02-01225183410.3390/s22051834A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling FlowsMuhammad Awais Sattar0Matheus Martinez Garcia1Luis M. Portela2Laurent Babout3Institute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18/22, 90-924 Lodz, PolandDepartment of Chemical Engineering, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The NetherlandsDepartment of Chemical Engineering, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The NetherlandsInstitute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18/22, 90-924 Lodz, PolandElectrical 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 10<sup>4</sup> 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.https://www.mdpi.com/1424-8220/22/5/1834electrical resistance tomography (ERT)raw data processinginline swirl separatorgeometrical parameter extraction |
| spellingShingle | Muhammad Awais Sattar Matheus Martinez Garcia Luis M. Portela Laurent Babout A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows Sensors electrical resistance tomography (ERT) raw data processing inline swirl separator geometrical parameter extraction |
| title | A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows |
| title_full | A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows |
| title_fullStr | A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows |
| title_full_unstemmed | A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows |
| title_short | A Fast Electrical Resistivity-Based Algorithm to Measure and Visualize Two-Phase Swirling Flows |
| title_sort | fast electrical resistivity based algorithm to measure and visualize two phase swirling flows |
| topic | electrical resistance tomography (ERT) raw data processing inline swirl separator geometrical parameter extraction |
| url | https://www.mdpi.com/1424-8220/22/5/1834 |
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