There　are　problems　in　that　the　Raman　analysis　of　transformer　oil　is　usually　interfered　with　by　noise　and　fluorescent　background,　and　it　is　difficult　to　identify　the　position　of　the　spectral　peak.　Thus　this　paper　proposes　an　improved　data　processing　and　spectral　peak　recognition　algorithm　for　the　Raman　analysis　of　transformer　oil　aging　evaluation.　An　adaptive　Savitzky-Golay　filtering　method　is　proposed,　and　adaptive　window-size　Raman　spectral　data　is　introduced　for　denoising.　An　improved　polynomial　fitting　algorithm　is　used　to　remove　the　fluorescence　background　processing　of　the　de-noised　data　to　reduce　its　influence　on　the　fitting　results.　Each　data　point　is　weighted　according　to　the　distance　between　the　data　point　and　the　expected　Raman　signal,　so　as　to　achieve　more　accurate　de-fluorescence　background　processing.　The　aging　degree　of　transformer　oil　is　identified　by　spectral　peak　recognition　technology,　and　the　spectral　peak　is　identified　by　the　Gaussian　window　discrimination　method　with　two　scales,　and　the　authenticity　of　the　suspected　Raman　spectral　peak　is　judged　by　the　local　weighted　signal-to-noise　ratio　(LW_SNR).　Finally,　the　effectiveness　of　the　proposed　algorithm　in　transformer　oil　aging　evaluation　is　proved　by　experiment.　©　2024　Power　System　Protection　and　Control　Press.　All　rights　reserved.