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Fault detection and diagnosis for process control rig using artificial intelligent


Citation

Yusof, Rubiyah and Abdul Rahman, Ribhan Zafira and Khalid, Marzuki (2010) Fault detection and diagnosis for process control rig using artificial intelligent. ICIC Express Letters, 4 (5B). pp. 1811-1816. ISSN 1881-803X

Abstract

This paper focuses on the application of artificial intelligent techniques in fault detection and diagnosis. The objective of this paper is to detect and diagnose the faults to a process control rig. Fuzzy logic with genetic algorithm method is used to develop fault model and to detect the fault where this task 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. Meanwhile, neural network is used for fault classification where this task is performed by identifying the fault in the system.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Publisher: ICIC International
Keywords: Fault detection and diagnosis; Fuzzy logic; Genetic algorithms; Neural network; Process control
Depositing User: Nabilah Mustapa
Date Deposited: 14 Aug 2015 12:29
Last Modified: 30 Oct 2015 00:37
URI: http://psasir.upm.edu.my/id/eprint/14736
Statistic Details: View Download Statistic

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