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Detection and interactive isolation of faults in steam turbines to support maintenance decisions
Mälardalen University, Department of Public Technology.
2008 (English)In: Simulation (San Diego, Calif.), ISSN 1569-190X, E-ISSN 1878-1462, Vol. 16, no 10, 1689-1703 p.Article in journal (Refereed) Published
Abstract [en]

The maintenance of steam turbines is expensive, particularly if dismantling is required. A concept for the provision Of Support for the maintenance engineer in determining steam turbine status in relation to the recommended maintenance interval is presented here. The concept embodies an artificial neural network which is conditioned to recognise patterns known to be related to faults. The faults Simulated are not known to be recognized on-line and the concept is in an early stage of development, An example of a Bayesian network structure containing expert knowledge is proposed to be used, in a dialogue with the operator, to isolate the root causes of a number Of fault types. The aim is to be well informed about the statue of the turbine in order to take earlier and better informed maintenance actions. The detection procedure has been validated in a Simulation environment.

Place, publisher, year, edition, pages
2008. Vol. 16, no 10, 1689-1703 p.
Keyword [en]
Steam turbine maintenance, Artificial neural network fault detection, Bayesian network fault isolation, Decision support
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-19356DOI: 10.1016/j.simpat.2008.08.013ISI: 000261701200013Scopus ID: 2-s2.0-55249123555OAI: oai:DiVA.org:mdh-19356DiVA: diva2:632796
Available from: 2013-06-25 Created: 2013-06-20 Last updated: 2013-06-25Bibliographically approved

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Citation style
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