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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259673
