The　time-frequency　analysis　method　can　extend　a　one-dimensional　signal　to　a　two-dimensional　time-frequency　plane,　revealing　the　signal＇s　time-varying　characteristics.　The　time-frequency　representation　(TFR)　obtained　by　the　time-frequency　postprocessing　algorithm　has　the　characteristics　of　energy　aggregation　and　high　resolution.　The　generalized　S-synchroextracting　transform　(GS-SET)　stands　out　for　its　strong　adaptability.　However,　this　method　cannot　obtain　effective　information　when　analyzing　multicomponent　complex　signals.　We　propose　an　enhanced　time-frequency　analysis　method　to　solve　this　problem.　First,　the　multicomponent　complex　signal　is　decomposed　into　multiple　mono-component　signals　by　the　Vold-Kalman　time-varying　filtering　technique.　Second,　these　signals　are　processed　by　the　GS-SET　method.　Last,　the　obtained　TFRs　are　linearly　superimposed　to　obtain　the　results　of　the　enhanced　method.　The　simulated　signal　verifies　that　the　proposed　method　can　effectively　represent　its　time-varying　characteristics.　The　experimental　signal　of　the　rolling　bearing　verifies　the　practicability　of　this　method.