Fault diagnosis method for hydroelectric units based on rough set & Rbf network
Luo Xingqi · Journal of Northwest A&F University · 2007
Due to the excessive data of monitoring and the complexity of fault reason for hydroelectric units,the problems exist in neural network when it is used for the fault diagnosis of hydroelectric units,such as the complex structure,the long training time and the difficult diagnosis.The rough set theory is introduced and the fault diagnosis method for hydroelectric units based on rough set RBF neural network is presented.The fault information of hydroelectric units is reduced by the rough set theory on the basis of classifying capability unchanged,then the information is diagnosed by RBF neural network,which not only decreases the number of the network input nerve cells effectively,but also predigests the network structure.The application of an example proves that the proposed method can improve the accuracy and the efficiency of fault diagnosis of hydroelectric units.