Soft Sensor for NOx Emission using Dynamical Neural Network

In this paper we propose a soft sensor for prediction of NOx emission from the combustion unit of industrial boilers. The soft sensor is based on a dynamical neural network model. A simplified structure of the dynamical neural network model is achieved by grouping the input variables using basic kno...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Shakil, M. (author)
مؤلفون آخرون: Elshafei, M. (author), Habib, M. A. (author), Al-Maleki, F. (author), unknown (author)
التنسيق: article
منشور في: 2020
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/1457/1/d2_s9_p4_1569043201.pdf
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
_version_ 1864513389545390080
author Shakil, M.
author2 Elshafei, M.
Habib, M. A.
Al-Maleki, F.
unknown
author2_role author
author
author
author
author_facet Shakil, M.
Elshafei, M.
Habib, M. A.
Al-Maleki, F.
unknown
author_role author
dc.creator.none.fl_str_mv Shakil, M.
Elshafei, M.
Habib, M. A.
Al-Maleki, F.
unknown
dc.date.*.fl_str_mv 2020
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/1457/1/d2_s9_p4_1569043201.pdf
Soft Sensor for NOx Emission using Dynamical Neural Network. IEEEGCC 2007.
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/1457/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.title.none.fl_str_mv Soft Sensor for NOx Emission using Dynamical Neural Network
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description In this paper we propose a soft sensor for prediction of NOx emission from the combustion unit of industrial boilers. The soft sensor is based on a dynamical neural network model. A simplified structure of the dynamical neural network model is achieved by grouping the input variables using basic knowledge of the system. Neural network model is trained using real data logs of an industrial boiler. Principal Component Analysis (PCA) is used to reduce number of input variables. Lag space for the model is found by using genetic algorithm to find the best time delayed model. Lag space obtained from the linear model is then used for constriction of the dynamical neural network. The proposed model is validated using different data from the same boiler and its ability to accurately predict NOx emission from the boiler is demonstrated.
eu_rights_str_mv openAccess
format article
id KFUPM_2b11ec7932276a35ab9f2fff4edf513e
identifier_str_mv Soft Sensor for NOx Emission using Dynamical Neural Network. IEEEGCC 2007.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::1457
publishDate 2020
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Soft Sensor for NOx Emission using Dynamical Neural NetworkShakil, M.Elshafei, M.Habib, M. A.Al-Maleki, F.unknownIn this paper we propose a soft sensor for prediction of NOx emission from the combustion unit of industrial boilers. The soft sensor is based on a dynamical neural network model. A simplified structure of the dynamical neural network model is achieved by grouping the input variables using basic knowledge of the system. Neural network model is trained using real data logs of an industrial boiler. Principal Component Analysis (PCA) is used to reduce number of input variables. Lag space for the model is found by using genetic algorithm to find the best time delayed model. Lag space obtained from the linear model is then used for constriction of the dynamical neural network. The proposed model is validated using different data from the same boiler and its ability to accurately predict NOx emission from the boiler is demonstrated.ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/1457/1/d2_s9_p4_1569043201.pdf Soft Sensor for NOx Emission using Dynamical Neural Network. IEEEGCC 2007. enhttps://eprints.kfupm.edu.sa/id/eprint/1457/2020info:eu-repo/semantics/openAccessoai::14572019-11-01T13:27:02Z
spellingShingle Soft Sensor for NOx Emission using Dynamical Neural Network
Shakil, M.
status_str publishedVersion
title Soft Sensor for NOx Emission using Dynamical Neural Network
title_full Soft Sensor for NOx Emission using Dynamical Neural Network
title_fullStr Soft Sensor for NOx Emission using Dynamical Neural Network
title_full_unstemmed Soft Sensor for NOx Emission using Dynamical Neural Network
title_short Soft Sensor for NOx Emission using Dynamical Neural Network
title_sort Soft Sensor for NOx Emission using Dynamical Neural Network
url https://eprints.kfupm.edu.sa/id/eprint/1457/1/d2_s9_p4_1569043201.pdf