Fault detection and diagnosis for continuous stirred tank reactor using neural network
The paper focuses on the application of neural network techniques in fault detection and diagnosis. The objective of this paper is to detect and diagnose the faults to a continuous stirred tank reactor (CSTR). Fault detection is performed by using the error signals, where when error signal is zero o...
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Kathmandu University
2010
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Online Access: | http://psasir.upm.edu.my/id/eprint/14734/1/Fault%20detection%20and%20diagnosis%20for%20continuous%20stirred%20tank%20reactor%20using%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/14734/ http://www.ku.edu.np/kuset/index.php?go=vol6_no2 |
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my.upm.eprints.147342015-10-22T03:48:08Z http://psasir.upm.edu.my/id/eprint/14734/ Fault detection and diagnosis for continuous stirred tank reactor using neural network Abdul Rahman, Ribhan Zafira Che Soh, Azura Muhammad, Noor Fadzlina The paper focuses on the application of neural network techniques in fault detection and diagnosis. The objective of this paper is to detect and diagnose the faults to a continuous stirred tank reactor (CSTR). Fault detection is performed by using the error signals, where when error signal is zero or nearly zero, the system is in normal condition, and when the fault occurs, error signals should distinctively diverge from zero. The fault diagnosis is performed by identifying the amplitude error of the CSTR output error. Kathmandu University 2010-11 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/14734/1/Fault%20detection%20and%20diagnosis%20for%20continuous%20stirred%20tank%20reactor%20using%20neural%20network.pdf Abdul Rahman, Ribhan Zafira and Che Soh, Azura and Muhammad, Noor Fadzlina (2010) Fault detection and diagnosis for continuous stirred tank reactor using neural network. Kathmandu University Journal of Science, Engineering and Technology, 6 (2). pp. 66-74. ISSN 1816-8752 http://www.ku.edu.np/kuset/index.php?go=vol6_no2 |
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The paper focuses on the application of neural network techniques in fault detection and diagnosis. The objective of this paper is to detect and diagnose the faults to a continuous stirred tank reactor (CSTR). Fault detection is performed by using the error signals, where when error signal is zero or nearly zero, the system is in normal condition, and when the fault occurs, error
signals should distinctively diverge from zero. The fault diagnosis is performed by identifying the amplitude error of the CSTR output error. |
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Article |
author |
Abdul Rahman, Ribhan Zafira Che Soh, Azura Muhammad, Noor Fadzlina |
spellingShingle |
Abdul Rahman, Ribhan Zafira Che Soh, Azura Muhammad, Noor Fadzlina Fault detection and diagnosis for continuous stirred tank reactor using neural network |
author_facet |
Abdul Rahman, Ribhan Zafira Che Soh, Azura Muhammad, Noor Fadzlina |
author_sort |
Abdul Rahman, Ribhan Zafira |
title |
Fault detection and diagnosis for continuous stirred tank reactor using neural network |
title_short |
Fault detection and diagnosis for continuous stirred tank reactor using neural network |
title_full |
Fault detection and diagnosis for continuous stirred tank reactor using neural network |
title_fullStr |
Fault detection and diagnosis for continuous stirred tank reactor using neural network |
title_full_unstemmed |
Fault detection and diagnosis for continuous stirred tank reactor using neural network |
title_sort |
fault detection and diagnosis for continuous stirred tank reactor using neural network |
publisher |
Kathmandu University |
publishDate |
2010 |
url |
http://psasir.upm.edu.my/id/eprint/14734/1/Fault%20detection%20and%20diagnosis%20for%20continuous%20stirred%20tank%20reactor%20using%20neural%20network.pdf http://psasir.upm.edu.my/id/eprint/14734/ http://www.ku.edu.np/kuset/index.php?go=vol6_no2 |
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