Research on Optimization Method of Cleaning Parameters of Insulator Dry Ice Cleaning Robot

Abstract

Due to the influence of natural conditions such as rain and fog, the pillar insulators of substations accumulate a large amount of pollution on their surface to form a pollution layer, which can easily cause pollution flashover and seriously affect the operation safety of the substation. Based on the developed dry ice cleaning robot, this paper uses BP neural network combined with bat optimization algorithm to establish an insulator dry ice cleaning parameter optimization model, and optimizes the cleaning parameters with the goal of meeting the requirements of the cleaning effect and minimizing the consumption of dry ice. By collecting natural pollution A comparison test of the effect of manual pollution cleaning was carried out to confirm the adhesion of the pollution, and the parameters were input to the optimization model to obtain the optimal cleaning parameter combination. Experiments show that the proposed method improves the efficiency and cost-effectiveness of insulator cleaning operations, and has good practical value.