Design of fault diagnosis expert system based on fault tree and production rules

Abstract

ObjectiveTo fully utilize the experience of nuclear power plant operation and management to assist nuclear power operators in fault diagnosis, a marine nuclear power plant fault diagnosis expert system is designed. MethodFirst, based on the logical consistency between fault trees and production rules, a method is proposed to transform fault tree knowledge into production rules. The knowledge base and inference machine of the expert system are then optimized by using a mixed forward and backward inference method, and a forward inference strategy is designed to simplify the inference process based on the minimum cut set and importance analysis results of the fault tree. Finally, based on the idea of manually judging the fault status, a status monitoring module is designed to collect key equipment parameters in real time and convert them into equipment information that can be recognized by expert systems. ResultsThe results show that the proposed method solves the problem of difficult knowledge acquisition in expert systems and improves inference efficiency while ensuring inference accuracy, thereby achieving the online fault diagnosis function of expert systems. ConclusionUsing the proposed method can enhance the knowledge acquisition ability and inference efficiency of expert systems, which is of great significance for ensuring the operational management safety of nuclear power plants.

Keywords

• nuclear power plant
• fault tree
• expert system
• production rule
• fault diagnosis