Cover Image

Fault detection and diagnosis for process control rig using artificial intelligent

The 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 wher...

Full description

Saved in:
Bibliographic Details
Main Authors: Khalid, Marzuki, R., Yusof, R., Abdul Rahman
Format: Article
Published: ICIC International 2010
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/26132/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.26132
record_format eprints
spelling my.utm.261322018-10-22T02:51:30Z http://eprints.utm.my/id/eprint/26132/ Fault detection and diagnosis for process control rig using artificial intelligent Khalid, Marzuki R., Yusof R., Abdul Rahman T Technology (General) The 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. ICIC International 2010 Article PeerReviewed Khalid, Marzuki and R., Yusof and R., Abdul Rahman (2010) Fault detection and diagnosis for process control rig using artificial intelligent. ICIC Express Letters, 4 (5 B). 1811 -1812. ISSN 1881-803X
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Khalid, Marzuki
R., Yusof
R., Abdul Rahman
Fault detection and diagnosis for process control rig using artificial intelligent
description The 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.
format Article
author Khalid, Marzuki
R., Yusof
R., Abdul Rahman
author_facet Khalid, Marzuki
R., Yusof
R., Abdul Rahman
author_sort Khalid, Marzuki
title Fault detection and diagnosis for process control rig using artificial intelligent
title_short Fault detection and diagnosis for process control rig using artificial intelligent
title_full Fault detection and diagnosis for process control rig using artificial intelligent
title_fullStr Fault detection and diagnosis for process control rig using artificial intelligent
title_full_unstemmed Fault detection and diagnosis for process control rig using artificial intelligent
title_sort fault detection and diagnosis for process control rig using artificial intelligent
publisher ICIC International
publishDate 2010
url http://eprints.utm.my/id/eprint/26132/
_version_ 1643647688603860992
score 13.159267

Similar Items