The fault diagnosis method for electrical equipment based on Bayesian network

Bayesian network offers a powerful map framework that can process probabilities inference. It can be used in inference and express of uncertainty knowledge. This paper introduce a new electrical equipment fault diagnosis method based on Bayesian network (BN). For example, power transformer is very important in power system as a electrical equipment. But, it´s very difficult to diagnose the fault exactly because power transformer´s complexity configuration. Now, dissolved gas analysis (DGA) is the most effective and convenient method in transformer fault diagnosis. However, the codes of DGA is too absolute, so this paper advances a new transformer fault diagnosis method based on Bayesian network (BN). This method introduces BN method into transformer fault diagnosis and presents a new idea of finding out transformer faults rapidly and exactly. Then, the transformer fault diagnosis model based on Bayesian network and DGA is constructed. Finally, the application examples in the fault diagnosis of transformer are given which shows that this method is effective.