Intelligent Fault Diagnosis of CINRAD Radar Based on Fault Tree and Bayesian Network

Abstract

In order to quickly and accurately identify the causes of the CINRAD radar faults, quickly troubleshoot them and make the radar return to normal operation. In this paper, an intelligent fault diagnosis method for the CINRAD radar was proposed by combining fault tree and Bayesian network. Firstly, a fault tree was constructed according to the constitution of the CINRAD radar and combined with a large number of fault cases, and then it was transformed into a Bayesian network model. finally, the CINRAD radar faults were quantitatively analyzed using Bayesian network and verified with actual maintenance cases of the CINRAD radar. The results showed that the fault diagnosis sequence values obtained by the fault diagnosis method designed in this paper were consistent with the actual maintenance sequence values, and the accuracy rate was 92.95%. The method can provide guidance for the fault maintenance of the CINRAD radar and has certain popularization value.