Flash-over voltage prediction of silicone rubber insulators under longitudinal and fan-shaped non-uniform pollution conditions

This paper proposes an Artificial Neural Network (ANN) model for AC flash-over voltage prediction of Silicone Rubber (SiR) insulators based on the experimental tests. In flash-over tests, the flash-over voltages of four different types of SiR insulators are measured under the uniform, longitudinal non-uniform, fan-shaped non-uniform and combined longitudinal, and fan-shaped non-uniform pollution conditions. The proposed ANN model is designed with six inputs data (insulator geometry and pollution parameters) and one output data (flash-over voltage). In order to validate the model, three different types of SiR insulators are tested under different pollution conditions. Then, their flash-over voltages are predicted using the proposed ANN model. The validation of the model shows that the absolute values of relative errors between flash-over voltages of test and prediction are less than 6%. This indicates a high efficiency of ANN technique in the flash-over voltage prediction of SiR insulators. (C) 2019 Elsevier Ltd. All rights reserved.