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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主要な著者: | Abdul Rahman, Ribhan Zafira, Che Soh, Azura, Muhammad, Noor Fadzlina |
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フォーマット: | 論文 |
言語: | English |
出版事項: |
Kathmandu University
2010
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オンライン・アクセス: | 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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