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A branch and bound method for fault isolation through missing variable analysis

Kariwala, V, Odiowei, P-E, Cao, Y and Chen, T (2010) A branch and bound method for fault isolation through missing variable analysis In: 9th International Symposium on Dynamics and Control of Process Systems, 2010-07-05 - 2010-07-07, Leuven, Belgium.

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Fault detection and diagnosis (FDD) is a critical approach to ensure safe and efficient operation of manufacturing and chemical processing plants. Multivariate statistical process monitoring (MSPM) has received considerable attention for FDD since it does not require a mechanistic process model. The diagnosis of the source or cause of the detected process fault in MSPM largely relies on contribution analysis, which is ineffective in identifying the joint contribution of multiple variables to the occurrence of fault. In this work, a missing variable analysis approach based on probabilistic principal component analysis is proposed for fault isolation. Furthermore, a branch and bound method is developed to handle the combinatorial nature of the problem involving finding the variables, which are most likely responsible for the occurrence of fault. The efficiency of the method proposed is shown through a case study on the Tennessee Eastman process.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions : Surrey research (other units)
Authors :
Kariwala, V
Odiowei, P-E
Cao, Y
Date : 5 July 2010
DOI : 10.3182/20100705-3-BE-2011.00021
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:12
Last Modified : 23 Jan 2020 17:42

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