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.　©2024　Chin.Soc.for　Elec.Eng.