Research on Anomaly Detection and Fault Diagnosis Technology for Complex Systems in Nuclear Power Plants Based on State Estimation

To achieve rapid detection and precise localization of minor faults in complex nuclear power plant systems (NPPS), this study first designed and built a predictive operation and maintenance technology test facility (hereafter referred to as the PHM test facility). Then, using nonlinear estimation and uncertainty analysis algorithms, an anomaly detection model was constructed. Finally, the operational data generated by test facility were used to test the proposed fault diagnosis technical scheme, which firstly employs a data-driven anomaly detection model to confirm the presence of anomalies, and then utilizes thermal-hydraulic analysis to localize faults. Results demonstrate that the PHM test facility can successfully produce controllable operational data of complex systems. The anomaly detection model can effectively identifiy system anomalies in a timely manner, while the fault diagnosis results obtained in thermal-hydraulic analysis for anomaly signal is consistent with the pre-injected faults in the test facility. This test facility addresses the current challenges in nuclear power applications where state estimation and anomaly detection algorithms predominantly rely on simulated data or operational data from other industrial scenarios for validation. Furthermore, it confirms the capability of the proposed fault diagnosis technical scheme to detect and localize minor faults for complex systems in NPPS.