Synchroextracting　transform　(SET)　is　a　time-frequency　(TF)　post-processing　algorithm　that　can　significantly　improve　the　readability　and　energy　aggregation　of　TFR,　but　it　has　the　drawbacks　of　uncertainty　in　window　width　selection　and　fixed　TF　resolution.　Based　on　this,　this　paper　proposes　a　new　time-frequency　analysis　(TFA)　method　named　Optimized　S　synchroextracting　transform　(OSSET).　This　algorithm　is　a　TFA　method　with　multi-time-frequency　resolution　and　adaptive　selection　of　optimal　parameter　set,　which　can　not　only　overcome　the　uncertainty　of　the　window　width　selection　and　the　fixed　TF　resolution　of　short　time　Fourier　transform,　but　also　overcome　the　shortcoming　of　the　local　frequency　dependence　of　S　transform.　Moreover,　the　improved　synchronous　extraction　operator　is　used　to　further　improve　the　energy　concentration　and　enhance　the　TF　readability.　The　analysis　results　of　simulation　signal　show　that　OSSET　can　more　clearly　and　accurately　represent　the　time-varying　characteristics　of　strong　frequency　modulation　signal　with　high　resolution,　and　has　higher　noise　robustness　than　SET　and　other　post-processing　algorithms.　Finally,　the　superiority　and　practicability　of　the　proposed　algorithm　are　further　demonstrated　in　the　applications　of　rolling　bearing　fault　experimental　data.　IEEE