A　new　denoising　method　based　on　dual-tree　complex　wavelet　transform　and　nonlinear　time　series　was　proposed,　considering　the　weakness,　such　as　the　phase　distortion,　of　the　wavelet　soft-threshold　denoising　method,　in　which　the　real　and　image　parts　of　the　coefficient　are　processed　individually.　The　new　method　process　the　magnitude　of　the　complex　coefficients　instead,　taking　into　account　the　fact　that　the　magnitude　does　not　oscillate　in　positive　and　negative　directions　which　is　more　suitable　for　threshold　denoising　and　the　fact　that　the　coefficients　of　the　fault　signal　are　always　periodic.　The　nonlinear　time　series　method　can　be　used　to　strengthen　the　periodicity　of　the　coefficients　caused　by　the　fault　signal　and　to　restrain　the　noise　meanwhile.　In　the　method　proposed,　the　fault　signal　was　decomposed　by　dual-tree　complex　wavelet　transform　to　obtain　the　coefficients　of　different　layers,　the　nonlinear　time　series　method　was　used　to　strengthen　the　periodicity　of　the　coefficient,　and　then　the　soft-threshold　denoising　was　carried　out　to　remove　the　DC　component.　Finally,　the　fault　characteristic　signal　was　obtained　by　coefficient　reconstruction.　The　simulation　and　experimental　results　show　the　effectiveness　of　the　method,　and　a　new　efficient　denoising　method　was　provided.　©,　2015,　Chinese　Vibration　Engineering　Society.　All　right　reserved.