Turbine Generating Units Fault Diagnosis of Based on the RBF Neutral Network
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Received
Revised
Published
2013-12-13
2013-12-16
2014-05-15
Issue Date
2015-04-09
Abstract
As turbine generator is effected by hydraulics, mechanical, electrical, and many other factors, it always has many complex failure, and these failures types often couple. This paper comprehensive analyzes of the subtractive clustering、K-Prototypes algorithm improved particle swarm optimization (PSO) algorithm,an algorithm of neural networks of Radial Basis Function is presented,establish a new RBF neural network model,and used it on the fault diagnosis of turbine generating unit. The simulation experiment results show that the classification accuracy rate and the stability of this model is higher and better.