When　a　single-phase-to-ground　(SPG)　fault　occurs　in　a　resonant　grounding　distribution　system,　the　amplitude　of　the　transient　zero-sequence　current　waveform　at　the　upstream　detection　node　of　the　fault　point　is　greater　than　the　amplitude　of　the　transient　zero-sequence　current　waveform　at　the　downstream　detection　node,　and　the　two　polarities　are　opposite.　The　transient　zero-sequence　currents　at　the　detection　nodes　on　the　same　side　of　the　fault　point　are　very　similar.　Based　on　this,　the　paper　proposes　a　new　method　of　SPG　fault　location　based　on　a　deep　belief　network　(DBN).　Firstly,　this　method　uses　the　fault　transient　zero-sequence　current　waveform　obtained　from　each　detection　node　in　the　simulation　model　as　the　input　of　DBN,　and　the　deep　features　of　the　fault　signals　are　extracted.　Secondly,　the　deep　features　are　divided　into　upstream　detection　nodes　category　and　downstream　detection　nodes　category　by　a　supervised　classifier.　And　then,　the　fault　location　is　implemented　by　analyzing　the　network　structure　of　fault　detection　nodes.　Finally,　the　testing　results　of　the　simulation　data　prove　that　the　algorithm　has　high　recognition　accuracy　under　different　fault　grounding　points,　different　initial　phase　angles　of　faults,　different　grounding　resistances,　and　different　types　of　faults,　and　has　certain　practical　engineering　application　value.　©　2022,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd.