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Bayesian network-based early-warning for leakage in recovery boilers
(PRO)
Mälardalen University, School of Sustainable Development of Society and Technology. (PRO)ORCID iD: 0000-0001-9230-1596
2008 (English)In: Applied Thermal Engineering, ISSN 1359-4311, E-ISSN 1873-5606, Vol. 28, no 7, p. 754-760Article in journal (Refereed) Published
Abstract [en]

Early-warning for leakage in a recovery boiler can help the process operator to detect faults and take action when a dangerous situation is developing. By analysing the mass-balances on both the steam and combustion side of the boiler in a Bayesian network, the probability of leakage can be determined and used as an early-warning. The method is tested with real plant data combined with leakage simulations. The results show that it is possible to detect considerably smaller leakages using this method than using the type of simple steam-side mass-balance method that is in use today. Bayesian network is an efficient tool to combine information from measurement signals and calculations giving an early-warning system that is robust to signal faults

Place, publisher, year, edition, pages
2008. Vol. 28, no 7, p. 754-760
Identifiers
URN: urn:nbn:se:mdh:diva-1161DOI: 10.1016/j.applthermaleng.2007.06.016ISI: 000253929900012Scopus ID: 2-s2.0-38849166596OAI: oai:DiVA.org:mdh-1161DiVA, id: diva2:37414
Available from: 2008-10-03 Created: 2008-10-03 Last updated: 2017-12-12Bibliographically approved

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Dotzauer, Erik

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