Accurate analysis of furfural concentration of oil-paper insulation ageing characteristics can be significant to assess the ageing of the operating transformers. Raman spectroscopy has been widely used in the field of material composition analysis and state diagnosis. In this paper, the quantitative analysis of dissolved furfural in transformer oil was carried out. Different furfural content of transformer oil samples were detected based on the Raman spectroscopy liquid test platform. After the efficient pretreatment, spectrum data was used principal component analysis method for data dimensionality reduction, and the establishment of furfural content dissolved in oil analysis regression model was based on support vector machine, the detection limit is 0.625 mg/L. The results show that the Raman spectroscopy combined support vector machine for quantitative analysis of furfural dissolved in transformer oil effectively, and it provides a new method for realizing a fast and accurate detection of dissolved matter in oil ageing characteristics.