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Fault diagnosis of an industrial gas turbine based on the t..:
Alblawi, Adel
gbv-ppn:1699015767. , 2020
Link:
http://hdl.handle.net/10419/244103
RT Journal T1
Fault diagnosis of an industrial gas turbine based on the thermodynamic model coupled with a multi feedforward artificial neural networks
UL https://suche.suub.uni-bremen.de/peid=base-ftzbwkiel:oai:econstor.eu:10419_244103&Exemplar=1&LAN=DE A1 Alblawi, Adel PB Amsterdam: Elsevier YR 2020 K1 ddc:330 K1 Energy efficiency K1 Engine performance and deterioration K1 Fault diagnosis K1 Industrial gas turbine K1 Multi feedforward artificial neural network K1 Thermodynamic model JF gbv-ppn:1699015767 LK http://hdl.handle.net/10419/244103 DO http://hdl.handle.net/10419/244103 SF ELIB - SuUB Bremen
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