Abstract: The main reason for the difference in surface flashover characteristics of insulators caused by the difference in pollution components is that glucose pollution is a special pollutionin the sugar producing areas in South China. Preliminary studies show that its strong hygroscopicity can facilitate the insulator discharge and flashover at a low relative humidity (75%). At present, the detection of such pollution as glucose can only be analyzed in laboratory by sampling, and there is a lack of on-site analysis means. Consequently, the rapid identification and quantitative detection of glucose contamination were studied by using laser-induced breakdown spectroscopy. In the experiments, 13 artificial contaminations with different glucose contents were taken as the main research object, and the sample spectra of glucose, sodium chloride, calcium and sulfate were collected to input into neural network for qualitative classification and identification. The recognition rate can reach 88%. Glucose pollution spectrum was pretreated by Lorentz multi-peak fitting, and the relationship between the spectral line intensity of O element and glucose content in the spectrum was quantitatively analyzed. The fitting degree was above 0.9, indicating that laser-induced breakdown spectroscopy can identify and quantitatively analyze artificial glucose pollution. This detection method can be adopted to quickly identify and quantitatively detect glucose contamination in the field, can improve the operation safety maintenance capacity of transmission lines, and has important engineering application value.