A Method of Fault Diagnosis for Secondary Loop in Intelligent Substation Based on Bayesian Algorithm

In order to improve the accuracy and maintenance efficiency of fault diagnosis for secondary loop in intelligent substation, this paper proposes a fault diagnosis method based on improved Bayesian algorithm. Firstly, the physical loop and virtual loop models of the secondary loop are established according to the SCD file, and their mapping relationship is established. Secondly, the set of suspicious fault components in the secondary loop is obtained according to the abnormal degree table of physical components. Then, the improved Bayesian algorithm is used to evaluate the components in the set of suspicious fault components. Finally, the output of the Bayesian algorithm is the Bayesian anomaly degree of the suspicious fault components. The component with the highest Bayesian anomaly degree is considered as the fault component. In order to detect the effectiveness and the feasibility of the proposed method, this paper conducts a fault diagnosis case and the diagnosis results demonstrate that the proposed diagnosis method can obtain good discriminant result.