Fault Detection and Isolation for In-core Self-powered Neutron Detectors Using Spatial-temporal Information Fusion
As the essential nuclear measurement equipment in new generation nuclear power plants,the self-powered neutron detector(SPND)plays a crucial role in ensuring the safe operation of reactors.The existing fault detection methods focus on time-domain analysis to build data-driven models,without leveraging the spatial coupling relationship of neutron flux in the reactor core.Therefore,an in-core SPND fault detection and isolation method integrating spatial-temporal information is proposed.First,the spatial-temporal graph data for SPND fault detection are established by combining SPND data with the layout of detector components within the reactor.Then,a real-time SPND fault detection model is designed using the graph convolution network-gate recurrent unit(GCN-GRU)and fault isolation(FI)strategy.Finally,using historical data and simulated fault samples from a pressurized water reactor,case analysis demonstrates that the method effectively fuses the spatial-temporal joint information of the overall SPNDs to reconstruct the current signals of individual SPNDs.The method can accurately detect and isolate faulty SPNDs,which exhibits higher accuracy and universality.
nuclear power plantself-powered neutron detectorfault detectionfault isolationgraph convolution networkgate recurrent unit
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