Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring

The present work presents a methodology based on data reconciliation to monitor<br />membrane separation processes reliably, online and in real time for the first time. The proposed methodology was implemented in accordance with the following steps: data acquisition; data pre-treatment; data c...

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Main Authors: Diego Q. F. de Q. F. de Menezes, Marília Caroline C. de Caroline C. de Sá, Tahyná B. B. Fontoura, Thiago K. K. Anzai, Fábio C. C. Diehl, Pedro H. H. Thompson, Jose Carlos Carlos Pinto
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Processes
Subjects:
Online Access:https://www.mdpi.com/2227-9717/8/9/1035
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spelling doaj-692976c9d9be4be1b9933f2e5f94207a2020-11-25T03:11:30ZengMDPI AGProcesses2227-97172020-08-0181035103510.3390/pr8091035Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online MonitoringDiego Q. F. de Q. F. de Menezes0Marília Caroline C. de Caroline C. de Sá1Tahyná B. B. Fontoura2Thiago K. K. Anzai3Fábio C. C. Diehl4Pedro H. H. Thompson5Jose Carlos Carlos Pinto6Programa de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro CEP 21941-972, RJ, BrazilPrograma de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro CEP 21941-972, RJ, BrazilPrograma de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro CEP 21941-972, RJ, BrazilCentro de Pesquisas Leopoldo Américo Miguez de Mello—CENPES, Petrobras—Petróleo Brasileiro SA, Rio de Janeiro CEP 21941-915, RJ, BrazilCentro de Pesquisas Leopoldo Américo Miguez de Mello—CENPES, Petrobras—Petróleo Brasileiro SA, Rio de Janeiro CEP 21941-915, RJ, BrazilCentro de Pesquisas Leopoldo Américo Miguez de Mello—CENPES, Petrobras—Petróleo Brasileiro SA, Rio de Janeiro CEP 21941-915, RJ, BrazilPrograma de Engenharia Química/COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro CEP 21941-972, RJ, BrazilThe present work presents a methodology based on data reconciliation to monitor<br />membrane separation processes reliably, online and in real time for the first time. The proposed methodology was implemented in accordance with the following steps: data acquisition; data pre-treatment; data characterization; data reconciliation; gross error detection; and critical evaluation of measured data with a soft sensor. The acquisition of data constituted the slowest<br />stage of the monitoring process, as expected in real-time applications. The pre-treatment stage was fundamental to assure the robustness of the code and the initial characterization of collected data<br />was carried out offline. The characterization of the data showed that steady-state modeling of the process would be appropriate, also allowing the implementation of faster numerical procedures for the data reconciliation step. The data reconciliation step performed well, quickly and consistently. Thus, data reconciliation allowed the estimation of unmeasured variables, playing the role of a soft sensor and allowing the future installation of a digital twin. Additionally, monitoring of measurement bias constituted a tool for measurement diagnosis. As shown in the manuscript, the proposed<br />methodology can be successfully implemented online and in real time for monitoring of membrane separation processes, as shown through a real dashboard web application developed for monitoring of an actual industrial site.https://www.mdpi.com/2227-9717/8/9/1035membranedata reconciliationreal-timeonlinemonitoring
collection DOAJ
language English
format Article
sources DOAJ
author Diego Q. F. de Q. F. de Menezes
Marília Caroline C. de Caroline C. de Sá
Tahyná B. B. Fontoura
Thiago K. K. Anzai
Fábio C. C. Diehl
Pedro H. H. Thompson
Jose Carlos Carlos Pinto
spellingShingle Diego Q. F. de Q. F. de Menezes
Marília Caroline C. de Caroline C. de Sá
Tahyná B. B. Fontoura
Thiago K. K. Anzai
Fábio C. C. Diehl
Pedro H. H. Thompson
Jose Carlos Carlos Pinto
Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
Processes
membrane
data reconciliation
real-time
online
monitoring
author_facet Diego Q. F. de Q. F. de Menezes
Marília Caroline C. de Caroline C. de Sá
Tahyná B. B. Fontoura
Thiago K. K. Anzai
Fábio C. C. Diehl
Pedro H. H. Thompson
Jose Carlos Carlos Pinto
author_sort Diego Q. F. de Q. F. de Menezes
title Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
title_short Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
title_full Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
title_fullStr Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
title_full_unstemmed Modeling of Spiral Wound Membranes for Gas Separations—Part II: Data Reconciliation for Online Monitoring
title_sort modeling of spiral wound membranes for gas separations—part ii: data reconciliation for online monitoring
publisher MDPI AG
series Processes
issn 2227-9717
publishDate 2020-08-01
description The present work presents a methodology based on data reconciliation to monitor<br />membrane separation processes reliably, online and in real time for the first time. The proposed methodology was implemented in accordance with the following steps: data acquisition; data pre-treatment; data characterization; data reconciliation; gross error detection; and critical evaluation of measured data with a soft sensor. The acquisition of data constituted the slowest<br />stage of the monitoring process, as expected in real-time applications. The pre-treatment stage was fundamental to assure the robustness of the code and the initial characterization of collected data<br />was carried out offline. The characterization of the data showed that steady-state modeling of the process would be appropriate, also allowing the implementation of faster numerical procedures for the data reconciliation step. The data reconciliation step performed well, quickly and consistently. Thus, data reconciliation allowed the estimation of unmeasured variables, playing the role of a soft sensor and allowing the future installation of a digital twin. Additionally, monitoring of measurement bias constituted a tool for measurement diagnosis. As shown in the manuscript, the proposed<br />methodology can be successfully implemented online and in real time for monitoring of membrane separation processes, as shown through a real dashboard web application developed for monitoring of an actual industrial site.
topic membrane
data reconciliation
real-time
online
monitoring
url https://www.mdpi.com/2227-9717/8/9/1035
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