The　operating　status　of　diesel　engine　changes　with　the　performance　degradation　of　valve　as　the　valve　clearance　gradually　increases　during　operation.　It　is　difficult　to　accurately　assessment　the　performance　degradation　status　of　valve　by　traditional　status　assessment　methods.　A　diesel　engine　valve　performance　degradation　status　assessment　method　based　on　synchroextracting　enhanced　generalized　Stransform　(SEEGST)　is　proposed.　The　vibration　signal　reflecting　the　status　of　diesel　engine　is　collected　by　sensors.　To　solve　the　problems　of　low　time-frequency　resolution　and　weak　energy　aggregation　in　traditional　signal　time-frequency　analysis　methods,　a　SEEGST　time-frequency　analysis　method　is　proposed　based　on　the　synchroextracting　algorithm　and　generalized　S-transform　to　convert　the　vibration　signal　into　a　two-dimensional　time-frequency　map.　MLP-Mixer　model　is　used　to　extract　the　time-frequency　image　features　for　training,　thus　realizing　the　assessment　of　diesel　engine　status.　The　proposed　method　is　compared　with　five　traditional　methods,　namely　SSGST-MLPMixer,　GST-MLPMixer,　SEEGST-ViT,　SEEGST-2DCNN　and　FFT　spectrum-1DCNN,　by　conducting　the　valve　performance　degradation　experiment　on　a　diesel　engine　status　monitoring　test　bench.　The　experimental　results　show　that　the　overall　assessment　accuracy　of　the　proposed　method　reaches　98.　96%,　which　can　be　effectively　applied　to　the　diesel　engine　valve　performance　degradation　status　assessment　and　provides　a　new　idea　for　conducting　the　diesel　engine　valve　performance　degradation　status　assessment.　©　2024　China　Ordnance　Industry　Corporation.　All　rights　reserved.