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Applications of object-oriented Bayesian networks for causal analysis of process disturbances

  • We discuss a hybrid approach for causal analysis of disturbances in industrial process operation. It represents a combination of OOBN with first level diagnostic packages and physical models serving as agents in the system design and providing evidence for automated reasoning on abnormality in process operation. The aim is causal analysis of non-measurable disturbances as a decision advice complement to the distributed control system (DCS). The approach includes prediction of signals' level-trend development, risk assessment for disturbance analysis and predictive maintenance on demand. The methodology has been applied on a screening process with a pressure-flow network in a Pulp Mil.

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Metadaten
Author:Galia WeidlORCiD, Anders L. Madsen, Erik Dahlquist
URL:https://www.researchgate.net/publication/228679172_Applications_of_object-oriented_Bayesian_networks_for_causal_analysis_of_process_disturbances#fullTextFileContent
Parent Title (English):SIMS'2003 (44th International Conference of the Scandinavian Simulation Society)
Document Type:Conference Proceeding
Language:English
Year of Completion:2003
Release Date:2023/12/07
Tag:Bayesian Networks; DCS; OOBN
GND Keyword:Prozessmodell; Prozesssteuerung
Urheberrecht:1
Institutes:Einrichtungen / Kompetenzzentrum Künstliche Intelligenz
research focus :Intelligent Systems / Artifical Intelligence and Data Science
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
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