LAUSR

In this paper, a method of aging diagnosis under different oil-paper ratios is proposed by investigating the accelerated thermal aging data with different oil-paper ratios. Aged oil-paper insulation samples with oil-paper ratios of 10:1, 15:1 and 20:1 are obtained by accelerated thermal aging tests. The Raman spectra of the transformer oil samples are measured by a Raman spectrometer, and screened by random forest algorithm to extract the features. A modified model is established to correcting the features of the aged oil samples under the conditions of 15:1 and 20:1 oil-paper ratio to features under the condition of 10:1 oil-paper ratio. An grid search optimized support vector machine (SVM) classification model is established, and verified by the corrected features. The experimental results show that the proposed method can effectively identify the aging of oil-paper insulation with different oil-paper ratios.