A concurrent fault diagnosis method for electric isolation valves in nuclear power plants based on rule-based reasoning and data-driven methods

Abstract

In order to improve the fault diagnosis ability of electric isolation valves in nuclear power plants, especially for the diagnosis of concurrent faults, a novel concurrent fault diagnosis method based on rule reasoning and data-driven methods is proposed in this study. The concurrent fault diagnosis method is divided into two layers: the rule-based reasoning layer and data-driven layer. In order to realize the diagnosis of most concurrent faults, the rule-based reasoning layer is established by a rule inference model according to the failure mode and effects analysis (FMEA) of the electric isolation valve. In order to diagnose concurrent faults with mutual interference of fault features that cannot be diagnosed by rule-based reasoning layer, the data-driven layer is established by variational mode decomposition (VMD) and fast independent component analysis (Fast-ICA) method to separate concurrent fault signals and gate recurrent unit (GRU) method to identify fault patterns. After testing on the electric valve test bench and simulation data, multiple concurrent faults of the electric isolation valve are diagnosed accurately by the proposed concurrent fault diagnosis framework, including complex concurrent faults such as internal leakage and external leakage, and the framework can also work in a single fault diagnosis scenario without changing models. Compared with the concurrent fault diagnosis based on multi-label support vector machine, the accuracy of concurrent fault diagnosis is improved by about 25.3%. The research can provide a new idea for the concurrent fault diagnosis of electric isolation valves and other equipment.