Recursive linear network modeling for detecting gas leak

In many industries, there are serious safety concerns related to the used of flammable gases in both indoor and outdoor environments. Any accidental and dispersion of toxic gases were always major hazards for public health and safety that industries had to deal with. Accident can happen due to many...

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Main Authors: Md Akib, Afifi, Saad, Nordin, Asirvadam, Vijanth
Format: Conference or Workshop Item
Published: 2010
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Online Access:http://eprints.utp.edu.my/4641/1/RecursiveGasLeak.pdf
http://eprints.utp.edu.my/4641/
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spelling my.utp.eprints.46412017-01-19T08:24:12Z Recursive linear network modeling for detecting gas leak Md Akib, Afifi Saad, Nordin Asirvadam, Vijanth TK Electrical engineering. Electronics Nuclear engineering In many industries, there are serious safety concerns related to the used of flammable gases in both indoor and outdoor environments. Any accidental and dispersion of toxic gases were always major hazards for public health and safety that industries had to deal with. Accident can happen due to many reasons, such as damaged pipes, leakage at storage tank, or while the gas being transport. For these reasons, it is crucial to develop reliable method of analyses of flammable gas release and dispersion. Relative mass loss of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithm. The objective of this paper is to describe the use of recursive solution in order to predict the release of mass flow rate using on-line data. Recursive Least Square (RLS) with different update scheme is used to predict the mass flow rate of the leakage and prediction error is observed. This paper proposed that, RLS algorithm model with Inversion Lemma update scheme can predict the release flow rate at very high accuracy comparatively and can to adopt the learning process very well. 2010-06 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/4641/1/RecursiveGasLeak.pdf Md Akib, Afifi and Saad, Nordin and Asirvadam, Vijanth (2010) Recursive linear network modeling for detecting gas leak. In: Intelligent and Advanced Systems (ICIAS), 2010 International Conference on. http://eprints.utp.edu.my/4641/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Md Akib, Afifi
Saad, Nordin
Asirvadam, Vijanth
Recursive linear network modeling for detecting gas leak
description In many industries, there are serious safety concerns related to the used of flammable gases in both indoor and outdoor environments. Any accidental and dispersion of toxic gases were always major hazards for public health and safety that industries had to deal with. Accident can happen due to many reasons, such as damaged pipes, leakage at storage tank, or while the gas being transport. For these reasons, it is crucial to develop reliable method of analyses of flammable gas release and dispersion. Relative mass loss of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithm. The objective of this paper is to describe the use of recursive solution in order to predict the release of mass flow rate using on-line data. Recursive Least Square (RLS) with different update scheme is used to predict the mass flow rate of the leakage and prediction error is observed. This paper proposed that, RLS algorithm model with Inversion Lemma update scheme can predict the release flow rate at very high accuracy comparatively and can to adopt the learning process very well.
format Conference or Workshop Item
author Md Akib, Afifi
Saad, Nordin
Asirvadam, Vijanth
author_facet Md Akib, Afifi
Saad, Nordin
Asirvadam, Vijanth
author_sort Md Akib, Afifi
title Recursive linear network modeling for detecting gas leak
title_short Recursive linear network modeling for detecting gas leak
title_full Recursive linear network modeling for detecting gas leak
title_fullStr Recursive linear network modeling for detecting gas leak
title_full_unstemmed Recursive linear network modeling for detecting gas leak
title_sort recursive linear network modeling for detecting gas leak
publishDate 2010
url http://eprints.utp.edu.my/4641/1/RecursiveGasLeak.pdf
http://eprints.utp.edu.my/4641/
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score 13.18916