@Article{EE.2022.016899,
AUTHOR = {Sihua Wang, Junjun Wang, Lijun Zhou, Long Chen, Lei Zhao},
TITLE = {Research on Flashover Voltage Prediction of Catenary Insulator Based on CaSO<sub>4</sub> Pollution with Different Mass Fraction},
JOURNAL = {Energy Engineering},
VOLUME = {119},
YEAR = {2022},
NUMBER = {1},
PAGES = {219--236},
URL = {http://www.techscience.com/energy/v119n1/45659},
ISSN = {1546-0118},
ABSTRACT = {<p>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<sub>4</sub> mass fraction (<i>w</i>(CaSO<sub>4</sub>)), and T were taken as input parameters, 50% flashover voltage (<i>U</i><sub>50%</sub>) 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.</p>
},
DOI = {10.32604/EE.2022.016899}
}