Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0009-2509(03)00008-3
Title: Multi-linear model-based fault detection during process transitions
Authors: Bhagwat, A.
Srinivasan, R. 
Krishnaswamy, P.R. 
Keywords: Fault detection
Mathematical modeling
Process monitoring' Process control
Safety
Transient response
Issue Date: May-2003
Source: Bhagwat, A., Srinivasan, R., Krishnaswamy, P.R. (2003-05). Multi-linear model-based fault detection during process transitions. Chemical Engineering Science 58 (9) : 1649-1670. ScholarBank@NUS Repository. https://doi.org/10.1016/S0009-2509(03)00008-3
Abstract: Process transitions due to startup, shutdown, product slate changes, and feedstock changes are frequent in the process industry. Experienced operators usually execute transitions in the manual mode as transitions may involve unusual conditions and nonlinear process behavior. Processes are therefore more prone to faults as well as inadvertent operator errors during transitions. Fault detection during transition is critical as faults can lead to abnormal situations and even cause accidents. This paper proposes a model-based fault detection scheme that involves decomposition of nonlinear transient systems into multiple linear modeling regimes. Kalman filters and open-loop observers are used for state estimation and residual generation based on the resulting linear models. Analysis of residuals using thresholds, faults tags, and logic charts enables on-line detection and isolation of faults. The multi-linear model-based fault detection technique has been implemented using Matlab and successfully tested to detect process faults and operator errors during the startup transition of highly nonlinear pH neutralization reactor in the laboratory. © 2003 Elsevier Science Ltd. All rights reserved.
Source Title: Chemical Engineering Science
URI: http://scholarbank.nus.edu.sg/handle/10635/66693
ISSN: 00092509
DOI: 10.1016/S0009-2509(03)00008-3
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

54
checked on Dec 7, 2017

WEB OF SCIENCETM
Citations

42
checked on Nov 22, 2017

Page view(s)

36
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.