Aiming　at　the　difficulty　of　early　weak　impactive　fault　feature　extraction　of　roller　bearings,　an　integrated　algorithm　based　on　resonance　demodulation　method　and　entropy　threshold　denoising　of　wavelet　packet　coefficients　is　proposed　to　accurately　determine　the　resonance　modulation　bands　resulted　by　early　weak　impactive　fault　signals.　Firstly,　the　algorithm　uses　delayed　correlation　pretreatment　and　entropy　threshold　arithmetic　of　wavelet　packet　coefficients　to　realize　double　noise　reduction　of　the　signals.　In　the　algorithm,　the　optimal　decomposition　scale　of　wavelet　packet　decomposition　and　optimal　entropy　threshold　are　chosen　based　on　resonance　band　energy　ratio　to　locate　the　best　solution　of　resonance　bands.　Then　resonance　demodulation　is　applied　to　the　best　resonance　bands　to　extract　the　fault　signal　feature.　Experiment　data　analysis　results　prove　the　validity　and　practicability　of　the　proposed　method　for　early　weak　impactive　fault　feature　extraction　of　roller　bearings.