The　transient　zero-sequence　current　of　each　feeder　in　a　resonant　grounding　system　is　characterized　by　nonlinearity　and　nonstationarity　when　a　single-phase-to-ground　fault　occurs.　Because　there　is　a　significant　difference　between　the　fault　transient　zero-sequence　current　waveforms　of　the　fault　feeder　and　the　sound　feeders,　a　new　fault　feeder　detection　method　is　presented,　based　on　a　time-frequency　matrix　(TFM)　and　polarity　distribution　matrix　(PDM)　singular　values　clustering　algorithm.　By　applying　a　Hilbert-Huang　transform　band-pass　filter　and　waveform　transformation　to　the　transient　zero-sequence　current　waveform　of　each　feeder,　the　TFM　and　PDM　can　be　constructed,　which　are　decomposed　by　singular-value　decomposition　(SVD).　Moreover,　the　normalized　singular　values　of　the　TFM　and　PDM　are　merged　together　and　are　used　to　form　the　amplitude-polarity　feature　matrix　(APFM).　Thus,　the　feature　quantities　including　the　amplitude　and　polarity　information　of　each　fault　transient　zero-sequence　current　waveform　are　obtained.　Then,　fuzzy　c-means　clustering　is　applied　to　the　APFM　so　as　to　detect　the　fault　feeder　by　dividing　the　fault　feeder　and　sound　feeders　into　two　categories　without　a　certain　threshold　setting.　Simulations　were　carried　out　via　PACAD/EMTDC®　and　a　physical　system　under　various　kinds　of　fault　conditions　and　factors　including　asynchronous　sample,　two-point-grounding　fault,　and　arc　fault.　Simulated　results　show　that　the　proposed　method　has　the　characteristics　of　high　accuracy　and　reliability　in　earth　fault　feeder　detection.　©　2017　Elsevier　Ltd