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Model-Based Parameter Estimation for Fault Detection Using Multiparametric Programming

Mid, EC; Dua, V; (2017) Model-Based Parameter Estimation for Fault Detection Using Multiparametric Programming. Industrial & Engineering Chemistry Research , 56 (28) pp. 8000-8015. 10.1021/acs.iecr.7b00722. Green open access

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Abstract

Fault detection has become increasingly important for improving the reliability and safety of process systems. This paper presents a model-based fault detection methodology for nonlinear process systems. The objective of this work is to detect faults by estimating the model parameters using multiparametric programming. The parameter estimates are obtained as an explicit function of the measurements by using multiparametric programming. The diagnosis of fault is carried out by monitoring the changes in the residual of model parameters. Case studies of fault detection for a single stage evaporator system and quadruple tank system are presented. A number of faulty and fault-free scenarios are considered to show the effectiveness of the presented approach. The proposed approach successfully estimates the model parameters and detects the faults through a simple function evaluation of explicit functions.

Type: Article
Title: Model-Based Parameter Estimation for Fault Detection Using Multiparametric Programming
Open access status: An open access version is available from UCL Discovery
DOI: 10.1021/acs.iecr.7b00722
Publisher version: http://doi.org/10.1021/acs.iecr.7b00722
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Parameter estimation, fault detection, multiparametric programming
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/1560288
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