Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0009-2509(03)00008-3
DC FieldValue
dc.titleMulti-linear model-based fault detection during process transitions
dc.contributor.authorBhagwat, A.
dc.contributor.authorSrinivasan, R.
dc.contributor.authorKrishnaswamy, P.R.
dc.date.accessioned2014-10-09T09:56:55Z
dc.date.available2014-10-09T09:56:55Z
dc.date.issued2003-05
dc.identifier.citationBhagwat, 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
dc.identifier.issn00092509
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/92154
dc.description.abstractProcess 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0009-2509(03)00008-3
dc.sourceScopus
dc.subjectFault detection
dc.subjectMathematical modeling
dc.subjectProcess monitoring' Process control
dc.subjectSafety
dc.subjectTransient response
dc.typeArticle
dc.contributor.departmentCHEMICAL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1016/S0009-2509(03)00008-3
dc.description.sourcetitleChemical Engineering Science
dc.description.volume58
dc.description.issue9
dc.description.page1649-1670
dc.description.codenCESCA
dc.identifier.isiut000182786100001
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