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Research on Flashover Voltage Prediction of Catenary Insulator Based on CaSO_(4) Pollution with Different Mass Fraction

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Energy Engineering 2022年第1期119卷 219-236页

作者： Sihua Wang Junjun Wang Lijun Zhou Long Chen Lei Zhao College of Automation&Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China Rail Transit Electrical Automation Engineering Laboratory of Gansu Province Lanzhou Jiaotong UniversityLanzhou730070China

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,CaSO_(4) mass fraction(w(CaSO_(4))),and T were taken as input parameters,50%flashover voltage(U_(50%))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.

关键词： overhead contact system w(CaSO_(4)) insulator pollution flashover test genetic algorithm-back propagation(GA-BP)neural network flashover voltage prediction

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