Qualitative simulation of chemical process systems: Steady‐state analysis
TL;DR: In this paper, the mauvais fonctionnement and l'effet des erreurs se propagent par causalite d'une variable a l'autre, en satisfaisant finalement les contraintes du procede en regime permanent.
Abstract: Dans une analyse qualitative le mauvais fonctionnement et l'effet des erreurs se propagent par causalite d'une variable a l'autre, en satisfaisant finalement les contraintes du procede en regime permanent. Les contraintes des series d'equations algebriques, sont representees par des equations de confluence stationnaires. La causalite est representee par le graphe oriente signe etendu (Extended Signed Directed Graph: ESDG)
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TL;DR: This three part series of papers is to provide a systematic and comparative study of various diagnostic methods from different perspectives and broadly classify fault diagnosis methods into three general categories and review them in three parts.
2,263 citations
TL;DR: This part of the paper reviews qualitative model representations and search strategies used in fault diagnostic systems and broadly classify them as topographic and symptomatic search techniques.
1,415 citations
Cites methods from "Qualitative simulation of chemical ..."
...Algorithms for identifying IVs and CVs have been given (Oyeleye & Kramer, 1988)....
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...Once all the additional arcs are drawn, the resulting SDG is called the Extended SDG (ESDG) (Oyeleye & Kramer, 1988)....
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...In negative feedback loops, nodal balance on ESDG automatically ensures the presence of SCPs (only SCPs) because invoking a complex path results in violation of at least one nodal balance at steady state....
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...Algorithms for identifying IVs and CVs have been given ( Oyeleye & Kramer, 1988 )....
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...ESDG can be converted into equivalent set of confluences using nodal balance (on nodes with at least one input arc)....
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01 Jul 1991
TL;DR: A multilayer perceptron network with a hyperbolic tangent as the nonlinear element seems best suited for the task of fault diagnosis in a realistic heat exchanger-continuous stirred tank reactor system.
Abstract: Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural network architectures for fault diagnosis are studied. The multilayer perceptron network with a hyperbolic tangent as the nonlinear element seems best suited for the task. As a test case, a realistic heat exchanger-continuous stirred tank reactor system is studied. The system has 14 noisy measurements and 10 faults. The proposed neural network was able to learn the faults in under 3000 training cycles and then to detect and classify the faults correctly. Principal component analysis is used to illustrate the fault diagnosis problem in question. >
300 citations
TL;DR: In this paper, the authors present a state-of-the-art review of the available techniques and methodologies for carrying out risk analysis in chemical process industries and present a set of methodologies developed by the authors to conduct risk analysis effectively and optimally.
Abstract: This paper presents a state-of-art-review of the available techniques and methodologies for carrying out risk analysis in chemical process industries. It also presents a set of methodologies developed by the authors to conduct risk analysis effectively and optimally.
284 citations
TL;DR: A realistic heat exchanger-continuous stirred tank reactor system is studied as a test case and the fault detection and diagnosis is based on the classification of process measurements and the classification is carried out using neural networks.
211 citations