Fault diagnosis of an industrial gas turbine based on the thermodynamic model coupled with a multi feedforward artificial neural networks
In the study presented in this paper, the deterioration in the performance of an industrial gas turbine during the operation design point was simulated by using the thermodynamic principle and a multi feedforward artificial neural networks (MFANN) system. Initially the thermodynamic model was constr...
Main Author: | Adel Alblawi |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-11-01
|
Series: | Energy Reports |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484720301177 |
Similar Items
-
IMPACT OF DEFECTS ON MULTILAYER ARTIFICIAL FEEDFORWARD NEURAL NETWORK OPERABILITY
by: Daniil V. Marshakov, et al.
Published: (2018-07-01) -
IMPACT OF DEFECTS ON MULTILAYER ARTIFICIAL FEEDFORWARD NEURAL NETWORK OPERABILITY
by: Daniil V. Marshakov, et al.
Published: (2011-03-01) -
Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance
by: Detang Zeng, et al.
Published: (2018-01-01) -
Condensation in gas turbine inlet ducts
by: Frey, David Alan
Published: (2007) -
Thermodynamic modelling and efficiency analysis of a class of real indirectly fired gas turbine cycles
by: Ma Zheshu, et al.
Published: (2009-01-01)