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Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control

Virtual sensing is crucial in order to provide feasible and economical alternatives when physical measuring instruments are not available. Developing model-based virtual sensors to calculate real-time information at each targeted location is a complex endeavor in terms of sensing technology. This pa...

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Autores principales: Guzmán, Cesar H., Carrera, José L., Durán, Héctor A., Berumen, Javier, Ortiz, Arturo A., Guirette, Omar A., Arroyo, Angélica, Brizuela, Jorge A., Gómez, Fabio, Blanco, Andrés, Azcaray, Héctor R., Hernández, Marlen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339024/
https://www.ncbi.nlm.nih.gov/pubmed/30586913
http://dx.doi.org/10.3390/s19010060
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author Guzmán, Cesar H.
Carrera, José L.
Durán, Héctor A.
Berumen, Javier
Ortiz, Arturo A.
Guirette, Omar A.
Arroyo, Angélica
Brizuela, Jorge A.
Gómez, Fabio
Blanco, Andrés
Azcaray, Héctor R.
Hernández, Marlen
author_facet Guzmán, Cesar H.
Carrera, José L.
Durán, Héctor A.
Berumen, Javier
Ortiz, Arturo A.
Guirette, Omar A.
Arroyo, Angélica
Brizuela, Jorge A.
Gómez, Fabio
Blanco, Andrés
Azcaray, Héctor R.
Hernández, Marlen
author_sort Guzmán, Cesar H.
collection PubMed
description Virtual sensing is crucial in order to provide feasible and economical alternatives when physical measuring instruments are not available. Developing model-based virtual sensors to calculate real-time information at each targeted location is a complex endeavor in terms of sensing technology. This paper proposes a new approach for model-based virtual sensor development using computational fluid dynamics (CFD) and control. Its main objective is to develop a three-dimensional (3D) real-time simulator using virtual sensors to monitor the temperature in a greenhouse. To conduct this study, a small-scale greenhouse was designed, modeled, and fabricated. The controller was based on the convection heat transfer equation under specific assumptions and conditions. To determine the temperature distribution in the greenhouse, a CFD analysis was conducted. Only one well-calibrated and controlled physical sensor (temperature reference) was enough for the CFD analysis. After processing the result that was obtained from the real sensor output, each virtual sensor had learned the associative transfer function that estimated the output from given input data, resulting in a 3D real-time simulator. This study has demonstrated, for the first time, that CFD analysis and a control strategy can be combined to obtain system models for monitoring the temperature in greenhouses. These findings suggest that, generally, virtual sensing can be applied in large greenhouses for monitoring the temperature using a 3D real-time simulator.
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spelling pubmed-63390242019-01-23 Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control Guzmán, Cesar H. Carrera, José L. Durán, Héctor A. Berumen, Javier Ortiz, Arturo A. Guirette, Omar A. Arroyo, Angélica Brizuela, Jorge A. Gómez, Fabio Blanco, Andrés Azcaray, Héctor R. Hernández, Marlen Sensors (Basel) Article Virtual sensing is crucial in order to provide feasible and economical alternatives when physical measuring instruments are not available. Developing model-based virtual sensors to calculate real-time information at each targeted location is a complex endeavor in terms of sensing technology. This paper proposes a new approach for model-based virtual sensor development using computational fluid dynamics (CFD) and control. Its main objective is to develop a three-dimensional (3D) real-time simulator using virtual sensors to monitor the temperature in a greenhouse. To conduct this study, a small-scale greenhouse was designed, modeled, and fabricated. The controller was based on the convection heat transfer equation under specific assumptions and conditions. To determine the temperature distribution in the greenhouse, a CFD analysis was conducted. Only one well-calibrated and controlled physical sensor (temperature reference) was enough for the CFD analysis. After processing the result that was obtained from the real sensor output, each virtual sensor had learned the associative transfer function that estimated the output from given input data, resulting in a 3D real-time simulator. This study has demonstrated, for the first time, that CFD analysis and a control strategy can be combined to obtain system models for monitoring the temperature in greenhouses. These findings suggest that, generally, virtual sensing can be applied in large greenhouses for monitoring the temperature using a 3D real-time simulator. MDPI 2018-12-24 /pmc/articles/PMC6339024/ /pubmed/30586913 http://dx.doi.org/10.3390/s19010060 Text en © 2018 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
Guzmán, Cesar H.
Carrera, José L.
Durán, Héctor A.
Berumen, Javier
Ortiz, Arturo A.
Guirette, Omar A.
Arroyo, Angélica
Brizuela, Jorge A.
Gómez, Fabio
Blanco, Andrés
Azcaray, Héctor R.
Hernández, Marlen
Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title_full Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title_fullStr Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title_full_unstemmed Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title_short Implementation of Virtual Sensors for Monitoring Temperature in Greenhouses Using CFD and Control
title_sort implementation of virtual sensors for monitoring temperature in greenhouses using cfd and control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339024/
https://www.ncbi.nlm.nih.gov/pubmed/30586913
http://dx.doi.org/10.3390/s19010060
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