An Improved Bayesian Algorithm in the Intelligent Substation Network Fault Diagnosis System
Zhou Fengl · Computer and Digital Engineering · 2014
To improve the fault diagnosis ability of the intelligent substation is very important for stable operation of power system and power supply reliability.One of the major problems that the power network fault diagnosis system faced is the fault classification problem.The existing classification algorithm has some shortcomings,such as the training samples imbalance,lack of consistent characteristics,weakness learning ability.The feature selection and learning strategies are added to Bayesian algorithm to propose an improved Bayesian fault classification algorithm.The experimental results show that the improved Bayesian algorithm can solve the fault classification problem effectively,and enhance the fault diagnosis capability of intelligent substation network.