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Why risk-based multivariate fault detection and diagnosis?

Citation

Zadakbar, O and Imtiaz, S and Khan, FI, Why risk-based multivariate fault detection and diagnosis?, Proceedings of the 10th IFAC International Symposium on Dynamics and Control of Process Systems, 18-20 December 2013, Mumbai, India, pp. 672-677. ISSN 1474-6670 (2013) [Refereed Conference Paper]

Copyright Statement

Copyright 2013 IFAC

DOI: doi:10.3182/20131218-3-IN-2045.00056

Abstract

A novel risk-based fault detection method has been developed. The proposed method provides a dynamic process risk indication based on the probability of happening a fault and its consequence. In this method instead of generating an alarm based on residuals or signals an alarm is activated only when the calculated risk of operation exceeds the acceptable threshold. This is an important concept as it can funnel the attention and effort of operators to the faults which poses the most operational or safety risk. Application of this new risk-based approach provides early warning of the fault as well as the associated risk with the fault. Methodologies were developed to apply the concept with model based fault detection algorithm as well as multivariate history based fault detection techniques. In this paper we show the model based approach by combining Kalman filter with the risk based approach. The history-based approach was demonstrated using principal component analysis (PCA). This method has more power in discerning between operational changes and abnormal conditions which have potential to cause accidents.

Item Details

Item Type:Refereed Conference Paper
Keywords:fault detection, principal component analysis, abnormal conditions, fault detection and diagnosis, fault detection techniques, model based approach, model-based fault detection, operational changes, risk based approaches, risk-based approach
Research Division:Engineering
Research Group:Interdisciplinary Engineering
Research Field:Risk Engineering (excl. Earthquake Engineering)
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Engineering
Author:Khan, FI (Professor Faisal Khan)
ID Code:120782
Year Published:2013
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-30
Last Modified:2017-10-17
Downloads:0

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