Rolling　bearings　often　work　under　nonstationary　conditions,　which　will　lead　to　spectrum　smearing　phenomenon　and　the　failure　of　traditional　diagnostic　methods.　Order　tracking　is　a　common　technique　to　alleviate　this　problem　by　resampling　the　time-domain　signal　using　the　instantaneous　rotation　frequency.　For　tacholess　applications,　it　is　of　great　importance　to　obtain　accurate　rotation　speeds.　In　this　paper,　a　tacholess　order　tracking　method　based　on　spectral　amplitude　modulation　(SAM)　is　proposed.　Based　on　the　fact　that　SAM　can　separate　frequency　components　with　different　levels　of　energy,　an　appropriate　weight　is　selected　to　highlight　the　instantaneous　frequency,　which　is　then　extracted　from　the　time-frequency　representation　by　peak　search　algorithm.　Moreover,　entropy　is　employed　to　evaluate　the　valuable　information　in　the　time-frequency　representation　in　order　to　select　an　optimal　weight　adaptively.　A　simulated　signal　and　experimental　signals　of　bearing　outer　and　inner　ring　faults　demonstrate　that　the　proposed　method　can　extract　instantaneous　rotation　frequency　and　detect　nonstationary　bearing　fault　characteristics　effectively.　IEEE