Publication
Identification of aircraft gas-turbines dynamics: comparison of classical and neural techniques
| dc.contributor.author | Lopes, J. C. | |
| dc.contributor.author | Ruano, Antonio | |
| dc.contributor.author | Fleming, P. J. | |
| dc.date.accessioned | 2013-02-12T11:07:39Z | |
| dc.date.available | 2013-02-12T11:07:39Z | |
| dc.date.issued | 2001 | |
| dc.date.updated | 2013-01-28T07:42:31Z | |
| dc.description.abstract | A gas turbine is made up of three basic components: a compressor, a combustion chamber and a turbine. Air is drawn into the engine by the compressor, which compresses it and delivers it to the combustion chamber. There, the air is mixed with the fuel and the mixture ignited, producing a rise of temperature and therefore an expansion of the gases. These are expelled through the engine nozzle, but first pass through the turbine, designed to extract energy to keep the compressor rotating [1]. The work described here uses data recorded from a Rolls Royce Spey MK 202 turbine, whose simplified diagram can be seen in Fig. 1. Both the compressor and the turbine are split into low pressure (LP) and high pressure (HP) stages. The HP turbine drives the HP compressor and the LP turbine drives the LP compressor. They are connected by concentric shafts that rotate at different speeds, denoted as NH and NL. | pt_PT |
| dc.identifier.citation | Lopes, J. C.; Ruano, A. E.; Fleming, P. J. Identification of Aircraft Gas-Turbines Dynamics: Comparison of Classical and Neural Techniques, Trabalho apresentado em Engineering Applications of Neural Networks (EANN’2001), In Engineering Applications of Neural Networks (EANN’2001), Cagliari, 2001. | por |
| dc.identifier.other | AUT: ARU00698; | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/2309 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.subject | Gas Turbines | por |
| dc.subject | Neural Networks | por |
| dc.subject | Systems Identification | por |
| dc.title | Identification of aircraft gas-turbines dynamics: comparison of classical and neural techniques | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Cagliari | por |
| oaire.citation.endPage | 2 | por |
| oaire.citation.startPage | 1 | por |
| oaire.citation.title | Engineering Applications of Neural Networks (EANN’2001) | por |
| person.familyName | Ruano | |
| person.givenName | Antonio | |
| person.identifier.orcid | 0000-0002-6308-8666 | |
| person.identifier.rid | B-4135-2008 | |
| person.identifier.scopus-author-id | 7004284159 | |
| rcaap.rights | restrictedAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | 13813664-b68b-40aa-97a9-91481a31ebf2 | |
| relation.isAuthorOfPublication.latestForDiscovery | 13813664-b68b-40aa-97a9-91481a31ebf2 |