Incorporating neural networks into gas turbine performance diagnostics

Kanelopoulos, K; Stamatis, A; Mathioudakis, K

dc.contributor.author	Kanelopoulos, K	en
dc.contributor.author	Stamatis, A	en
dc.contributor.author	Mathioudakis, K	en
dc.date.accessioned	2014-03-01T02:48:33Z
dc.date.available	2014-03-01T02:48:33Z
dc.date.issued	1997	en
dc.identifier.issn	04021215	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33886
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0031373667&partnerID=40&md5=303bc20eb84952f94b11981079a46ec3	en
dc.subject.other	Decision theory	en
dc.subject.other	Mathematical models	en
dc.subject.other	Neural networks	en
dc.subject.other	Sensors	en
dc.subject.other	Gas turbine diagnostics	en
dc.subject.other	Gas turbines	en
dc.title	Incorporating neural networks into gas turbine performance diagnostics	en
heal.type	conferenceItem	en
heal.publicationDate	1997	en
heal.abstract	Possibilities of incorporating neural nets in different tasks of a gas turbine performance diagnostic procedure are investigated. The purpose is to examine how neural nets can be implemented and what advantages they may offer. First, the possibility to constitute a performance model by using neural nets is considered. Different modes of operation are examined and the neural net architectures for achieving better accuracy are discussed. Subsequently, different problems of fault detection and identification are considered. Classification of faults is performed on the basis of diagnostic parameters produced by adaptive modelling. Both sensor faults and actual engine component faults are examined. A decision logic based on several neural nets is proposed. At a first level it is decided whether a fault exists, and if yes, checks are performed in order to identify the fault in as much detail as possible. Summarizing, the paper discusses different aspects of neural net implementation, in an effort to provide guidelines for application of this type of technique in the field of gas turbine diagnostics.	en
heal.publisher	ASME, New York, NY, United States	en
heal.journalName	American Society of Mechanical Engineers (Paper)	en