Title :
The simulation of failure parameter in a real time monitoring and analyzing system based on RBFN
Author :
Hu, Nun-su ; Zhao, Yu ; Wu, Jun-Fen
Author_Institution :
Sch. of Power & Mech. Eng., Wuhan Univ., China
Abstract :
A kind of method employing II type radial basis function neural networks (RBFNs) is proposed to deal with failure parameters in a real time monitoring and analyzing system for large machine units. This method can produce a simulated parameter to replace the failure parameter so that the reliability and veracity of the system can be improved greatly. Application to a steam turbine monitoring and analysis system is described.
Keywords :
condition monitoring; fault simulation; power system simulation; radial basis function networks; real-time systems; reliability theory; steam turbines; Il type radial basis function neural network; RBF neural network; economy index; failure parameter simulation; large machine units; real time monitoring; reliability; steam turbine monitoring; veracity; Analytical models; Condition monitoring; Electronic mail; Employment; Failure analysis; Humans; Mechanical engineering; Production systems; Radial basis function networks; Real time systems;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1174417
