DocumentCode
2489501
Title
Fault diagnosis of the steam turbine condenser system based on SOM neural network
Author
Hu, Nun-su ; He, Na-na ; Hu, Sheng
Author_Institution
Sch. of Power & Mech. Eng., Wuhan Univ., Hubei, China
Volume
2
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
1222
Abstract
The condenser system is one of the most important and complicated steam turbine thermodynamic systems. The SOM (self-organizing map) neural network is applied to fault diagnosis of the system, which is implemented by the neural network toolbox in MATLAB. The method for fault diagnosis of the condenser system is effective and it has been verified by simulation results.
Keywords
condensers (steam plant); failure analysis; fault diagnosis; self-organising feature maps; steam turbines; MATLAB; SOM neural network; fault diagnosis; neural network toolbox; self-organizing map; steam turbine condenser system; Electronic mail; Fault diagnosis; Helium; MATLAB; Mechanical engineering; Neural networks; Neurons; Power engineering and energy; Thermodynamics; Turbines;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259673
Filename
1259673
Link To Document