Research on Fault Diagnosis Method Based Rough Sets Theory and Neural Network
Wensheng Zou, Zhang Jianlin, Long Chengzhi · 2009
In allusion to more indeterminate information and higher speed request characteristic in fault diagnosis system, on the basis of switch and relay protecting information of substation, according to the intelligence complementary strategy, a new fault diagnosis method based on rough sets theory-neural network-expert system is presented. Firstly, basis on data acquisition and pretreatment, the original fault diagnosis samples are discretized by using hybrid clustering method. Then the decision attribute is reduced to delete redundancy information for obtaining the minimum fault feature subset. In course of the identifying fault diagnosis through RBF neural network, Some output results of RBF neural network is modified by using the inference capability expert system.