As　one　of　the　most　important　components　in　the　rotating　machinery,　the　rolling　bearing　will　affect　the　operation　precision　of　the　equipment,　the　running　state　of　the　gear,　the　degree　of　the　axis　and　even　cause　the　damage　of　the　equipment.　Therefore,　it　is　very　necessary　to　improve　the　processing　methods　of　non-stationary　signals.　In　this　paper,　an　adaptive　Kurtogram　(AK)　method　is　proposed.　The　greatest　advantage　of　this　method　is　the　use　of　the　order　statistics　filter　(OSF)　to　estimate　and　divide　the　effective　modal　components　from　the　spectrum　to　replace　the　fast　Kurtogram　(FK).　The　minimum　envelope　value　of　the　signal　in　frequency　domain　is　obtained　and　taken　as　the　boundaries.　Change　the　sliding　window　width　to　divide　different　boundaries　and　form　an　array.　The　empirical　wavelet　transform　(EWT)　is　used　to　reconstruct　the　signal　components　according　to　the　boundary　array.　Then　their　kurtosis　values　are　calculated.　The　frequency　band　with　the　largest　kurtosis　value　contains　the　impact　information,　and　the　corresponding　time　domain　component　presents　periodicity　impact.　AK　improves　the　shortcomings　of　the　center　frequency　and　the　bandwidth　of　the　fast　Kurtogram　(FK)　that　cannot　be　explained　theoretically.　The　method　of　dividing　the　boundaries　in　the　frequency　domain　is　optimized.　After　verification　by　the　simulated　signals　and　the　actual　signals,　this　method　is　faster　and　more　efficient.　(C)　2019　Elsevier　Ltd.　All　rights　reserved.