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Risk-based fault diagnosis and safety management for process systems


Bao, H and Khan, F and Iqbal, T and Chang, Y, Risk-based fault diagnosis and safety management for process systems, Process Safety Progress, 30, (1) pp. 6-17. ISSN 1066-8527 (2011) [Refereed Article]

DOI: doi:10.1002/prs.10421


An innovative methodology of risk-based fault diagnosis and its integration with safety instrumented system (SIS) is proposed in this article. The proposed methodology uses control chart technique to distinguish abnormal situation from normal operation based on three-sigma rule and linear trend forecast. Time series moving average techniques are used to perform real-time monitoring and noise filtering in fault diagnosis processes. Furthermore, risk indicators are used to identify and determine potential fault(s) to minimize the number of false alarms. The proposed methodology is implemented in G2 development environment. Two case studies of a tank filling system and a steam power plant system with SIS1s and SIS2s are conducted in G2 environment. A technique breakthrough from univariate monitoring to multivariate monitoring for fault diagnosis has been achieved during the verification in the steam power plant system. © 2010 American Institute of Chemical Engineers.

Item Details

Item Type:Refereed Article
Keywords:Fault diagnosis; G2 environment; Risk; Safety instrumented system; Safety management; Control charts; Development environment; Fault diagnosis; Filling system; G2 environment; Moving average technique; Multivariate monitoring; Noise filtering
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Ocean engineering
Objective Division:Mineral Resources (Excl. Energy Resources)
Objective Group:Environmentally sustainable mineral resource activities
Objective Field:Environmentally sustainable mineral resource activities not elsewhere classified
UTAS Author:Khan, F (Professor Faisal Khan)
ID Code:94523
Year Published:2011
Web of Science® Times Cited:14
Deposited By:Australian Maritime College
Deposited On:2014-09-11
Last Modified:2017-10-31

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