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Solid Concentration Estimation by Kalman Filter †
One of the major tasks in process industry is solid concentration (SC) estimation in solid–liquid two-phase flow in any pipeline. The γ-ray sensor provides the most used and direct measurement to SC, but it may be inaccurate due to very local measurements and inaccurate density baseline. Alternative...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248700/ https://www.ncbi.nlm.nih.gov/pubmed/32384782 http://dx.doi.org/10.3390/s20092657 |
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author | Tan, Yongguang Yue, Shihong |
author_facet | Tan, Yongguang Yue, Shihong |
author_sort | Tan, Yongguang |
collection | PubMed |
description | One of the major tasks in process industry is solid concentration (SC) estimation in solid–liquid two-phase flow in any pipeline. The γ-ray sensor provides the most used and direct measurement to SC, but it may be inaccurate due to very local measurements and inaccurate density baseline. Alternatively, under various conditions there are a tremendous amount of indirect measurements from other sensors that can be used to adjust the accuracy of SC estimation. Consequently, there is complementarity between them, and integrating direct and indirect measurements is helpful to improve the accuracy of SC estimation. In this paper, after recovering the interrelation of these measurements, we proposed a new SC estimation method according to Kalman filter fusion. Focusing on dredging engineering fields, SCs of representative flow pattern were tested. The results show that our proposed methods outperform the fused two types of measurements in real solid–liquid two-phase flow conditions. Additionally, the proposed method has potential to be applied to other fields as well as dredging engineering. |
format | Online Article Text |
id | pubmed-7248700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72487002020-08-13 Solid Concentration Estimation by Kalman Filter † Tan, Yongguang Yue, Shihong Sensors (Basel) Article One of the major tasks in process industry is solid concentration (SC) estimation in solid–liquid two-phase flow in any pipeline. The γ-ray sensor provides the most used and direct measurement to SC, but it may be inaccurate due to very local measurements and inaccurate density baseline. Alternatively, under various conditions there are a tremendous amount of indirect measurements from other sensors that can be used to adjust the accuracy of SC estimation. Consequently, there is complementarity between them, and integrating direct and indirect measurements is helpful to improve the accuracy of SC estimation. In this paper, after recovering the interrelation of these measurements, we proposed a new SC estimation method according to Kalman filter fusion. Focusing on dredging engineering fields, SCs of representative flow pattern were tested. The results show that our proposed methods outperform the fused two types of measurements in real solid–liquid two-phase flow conditions. Additionally, the proposed method has potential to be applied to other fields as well as dredging engineering. MDPI 2020-05-06 /pmc/articles/PMC7248700/ /pubmed/32384782 http://dx.doi.org/10.3390/s20092657 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tan, Yongguang Yue, Shihong Solid Concentration Estimation by Kalman Filter † |
title | Solid Concentration Estimation by Kalman Filter † |
title_full | Solid Concentration Estimation by Kalman Filter † |
title_fullStr | Solid Concentration Estimation by Kalman Filter † |
title_full_unstemmed | Solid Concentration Estimation by Kalman Filter † |
title_short | Solid Concentration Estimation by Kalman Filter † |
title_sort | solid concentration estimation by kalman filter † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248700/ https://www.ncbi.nlm.nih.gov/pubmed/32384782 http://dx.doi.org/10.3390/s20092657 |
work_keys_str_mv | AT tanyongguang solidconcentrationestimationbykalmanfilter AT yueshihong solidconcentrationestimationbykalmanfilter |