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Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant

Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artifi...

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Main Authors: Ismail, F.B., Thiruchelvam, V.
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Published: 2017
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/6393
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spelling my.uniten.dspace-63932017-12-08T09:35:58Z Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant Ismail, F.B. Thiruchelvam, V. Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artificial intelligent monitoring systems specialized in condenser outages has been proposed and coded within the MATLAB environment. The training and validation of the system has been performed using real operational measurements captured from the control system of selected steam power plant. An integrated plant data preparation scheme for condenser outages with related operational variables has been proposed. Condenser outages under consideration have been detected by developed system before the plant control system» © Published under licence by IOP Publishing Ltd. 2017-12-08T09:35:58Z 2017-12-08T09:35:58Z 2013 http://dspace.uniten.edu.my/jspui/handle/123456789/6393
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artificial intelligent monitoring systems specialized in condenser outages has been proposed and coded within the MATLAB environment. The training and validation of the system has been performed using real operational measurements captured from the control system of selected steam power plant. An integrated plant data preparation scheme for condenser outages with related operational variables has been proposed. Condenser outages under consideration have been detected by developed system before the plant control system» © Published under licence by IOP Publishing Ltd.
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author Ismail, F.B.
Thiruchelvam, V.
spellingShingle Ismail, F.B.
Thiruchelvam, V.
Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
author_facet Ismail, F.B.
Thiruchelvam, V.
author_sort Ismail, F.B.
title Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
title_short Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
title_full Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
title_fullStr Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
title_full_unstemmed Back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
title_sort back propagation artificial neural network and its application in fault detection of condenser failure in thermo plant
publishDate 2017
url http://dspace.uniten.edu.my/jspui/handle/123456789/6393
_version_ 1644493920944521216
score 13.160551

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