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Risk-based process system monitoring using self-organizing map integrated with loss functions


Yu, H and Khan, F and Garaniya, V, Risk-based process system monitoring using self-organizing map integrated with loss functions, Canadian Journal of Chemical Engineering, 94, (7) pp. 1295-1307. ISSN 1939-019X (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Canadian Society for Chemical Engineering

DOI: doi:10.1002/cjce.22480


The conventional dynamic risk assessment technique does not consider the effect of nonlinear interactions among process variables in its operational risk estimation. Thus, this type of technique fails to provide a realistic estimation of the operational risk of complex industrial processes. To address this issue, a multivariate risk-based process monitoring technique is proposed. This technique takes advantage of the powerful nonlinear dimensionality reduction and visualization power of the self-organizing map to identify the origin and propagation path of the fault. Through integration with the inverted normal loss function, a robust estimation of the hazard potential and operational risk of process operations can be achieved. The proposed technique is tested with two fault conditions in the benchmark Tennessee Eastman chemical process. The results show promising performance.

Item Details

Item Type:Refereed Article
Keywords:self-organizing map, process monitoring, loss quantification, real-time operational risk assessment
Research Division:Engineering
Research Group:Chemical engineering
Research Field:Process control and simulation
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Yu, H (Mr Hongyang Yu)
UTAS Author:Khan, F (Professor Faisal Khan)
UTAS Author:Garaniya, V (Associate Professor Vikram Garaniya)
ID Code:109771
Year Published:2016
Web of Science® Times Cited:7
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2016-06-30
Last Modified:2017-11-03

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