A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri

Heat exchangers are widely used in industry both for cooling and heating large scale industrial processes. This process offers a complete line of thermal fluid heat transfer systems. Therefore, much energy is required to operate this unit. Neural network tecniques have been applied to many thermal p...

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Main Authors:	Abdullah, Zalizawati, Kasmuri, Nor Hazelah
Format:	Research Reports
Language:	English
Published:	Research Management Institute (RMI) 2012
Subjects:	Neural networks (Computer science)
Online Access:	http://ir.uitm.edu.my/id/eprint/21022/ http://ir.uitm.edu.my/id/eprint/21022/1/LP_ZALIZAWATI%20ABDULLAH%20RMI%2012_5.pdf

id	uitm-21022
recordtype	eprints
spelling	uitm-210222018-10-08T07:38:46Z http://ir.uitm.edu.my/id/eprint/21022/ A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri Abdullah, Zalizawati Kasmuri, Nor Hazelah Neural networks (Computer science) Heat exchangers are widely used in industry both for cooling and heating large scale industrial processes. This process offers a complete line of thermal fluid heat transfer systems. Therefore, much energy is required to operate this unit. Neural network tecniques have been applied to many thermal problems, including the prediction of the steady-state and the dynamic behavior of heat exchangers. The neural network is used as a nonlinear process model to predict the future behavior of the controlled process i.e temperature outlet. The ability of neural network system to understand the behavior of this thermal process can lead to energy saving. In this study, the multiple neural network model will be developed to describe the nonlinear dynamic behavior of the heat exchanger. It is based on fact that multiple neural network model often giving improved performance compared to single network systems in terms of their accuracy and generalization capability. Experimental data will be collected from pilot plant heat exchanger equipped with Emerson DeltaV™ DCS in order to provide sufficient data processing to develop the model. The multiple multilayer perceptron neural network model of the heat exchanger will be developed in Matlab™ environment and the performance of the model developed will be assessed. Successful investigation will lead to availability of accurate models to represent the nonlinear dynamic behavior of heat exchanger that can be used in the development of advanced control system. Research Management Institute (RMI) 2012 Research Reports NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/21022/1/LP_ZALIZAWATI%20ABDULLAH%20RMI%2012_5.pdf Abdullah, Zalizawati and Kasmuri, Nor Hazelah (2012) A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri. [Research Reports] (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Neural networks (Computer science)
spellingShingle	Neural networks (Computer science) Abdullah, Zalizawati Kasmuri, Nor Hazelah A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
description	Heat exchangers are widely used in industry both for cooling and heating large scale industrial processes. This process offers a complete line of thermal fluid heat transfer systems. Therefore, much energy is required to operate this unit. Neural network tecniques have been applied to many thermal problems, including the prediction of the steady-state and the dynamic behavior of heat exchangers. The neural network is used as a nonlinear process model to predict the future behavior of the controlled process i.e temperature outlet. The ability of neural network system to understand the behavior of this thermal process can lead to energy saving. In this study, the multiple neural network model will be developed to describe the nonlinear dynamic behavior of the heat exchanger. It is based on fact that multiple neural network model often giving improved performance compared to single network systems in terms of their accuracy and generalization capability. Experimental data will be collected from pilot plant heat exchanger equipped with Emerson DeltaV™ DCS in order to provide sufficient data processing to develop the model. The multiple multilayer perceptron neural network model of the heat exchanger will be developed in Matlab™ environment and the performance of the model developed will be assessed. Successful investigation will lead to availability of accurate models to represent the nonlinear dynamic behavior of heat exchanger that can be used in the development of advanced control system.
format	Research Reports
author	Abdullah, Zalizawati Kasmuri, Nor Hazelah
author_facet	Abdullah, Zalizawati Kasmuri, Nor Hazelah
author_sort	Abdullah, Zalizawati
title	A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
title_short	A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
title_full	A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
title_fullStr	A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
title_full_unstemmed	A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri
title_sort	dynamic neural network based model predicting outlet temperature of heat exchanger / zalizawati abdullah and nor hazelah kasmuri
publisher	Research Management Institute (RMI)
publishDate	2012
url	http://ir.uitm.edu.my/id/eprint/21022/ http://ir.uitm.edu.my/id/eprint/21022/1/LP_ZALIZAWATI%20ABDULLAH%20RMI%2012_5.pdf
first_indexed	2023-09-18T23:05:39Z
last_indexed	2023-09-18T23:05:39Z
_version_	1777418465355759616

A dynamic neural network based model predicting outlet temperature of heat exchanger / Zalizawati Abdullah and Nor Hazelah Kasmuri

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