Fault Diagnosis Of Distributed Power Networks Based On Rough Set And Bayes Method

According to complementary strategy,a new power networks fault diagnosis method based on rough set and Bayes is presented for fault diagnosis containing redundancy and uncertain information.Furthermore, considering the limitations of traditional artificial intelligence technology in the fault diagnosis of large scale power networks, distributed thinking is used to solve the problem. What matters most is that the large scale power networks will be divided in a desired number of sub-networks. What also counts is that decision table is established by using rough sets theory in these sub-networks. And additonal factor worth mentioning is that the global rules base of sub-networks and tie lines is extracted by use of rough set and Bayes and the diagnostic rusults is obtained according to real-time alarm information. The results of tests show that the method is simple, efficient, rapid and good fault-tolerant.