Research on Flashover Voltage Prediction of Catenary Insulator Based on CaSO4 Pollution with Different Mass Fraction

Abstract

Pollution flashover accidents occur frequently in railway OCS in saline-alkali areas. To accurately predict the pollution flashover voltage of insulators, a pollution flashover warning should be made in advance. According to the operating environment of insulators along the Qinghai-Tibet railway, the pollution flashover experiments were designed for the cantilever composite insulator FQBG-25/12. Through the experiments, the flashover voltage under the influence of soluble contaminant density (SCD) of different pollution components, non-soluble deposit density (NSDD), temperature (T), and atmospheric pressure (P) was obtained. On this basis, the GA-BP neural network prediction model was established. P, SCD, NSDD, CaSO4 mass fraction (w(CaSO4)), and T were taken as input parameters, 50% flashover voltage (U50%) of the insulator was taken as output parameters. The results showed that the prediction deviation was less than 10%, which meets the basic engineering requirements. The results could not only provide early warning for the anti-pollution flashover work of the railway power supply department, but also be used as an auxiliary contrast to verify the accuracy of the results of the experiments, and provide a theoretical basis for the classification of pollution levels in different regions.