Polluted insulators at high voltages has

Polluted insulators at high voltages has acquired considerable importance with the rise of voltage transmission lines. The contamination may lead to flashover voltage. As a result, flashover voltage could lead to service outage and affects negatively the reliab ility of the power system. This paper pr esents a dynamic model of ac 50Hz flashover voltages of polluted hydrophobic polymer insulators. The models are constructed using the regression tree method, artificial neural network (ANN), and adaptive neuro -fuzzy (ANFIS). For this purpose, more than 2000 different experimental testing conditions were used to generate a training set. The study of the ac flashover voltages depends on silicone rub ber (SiR) percentage content in ethylene propylene diene monomer (EPDM) rub b er. Besides, water conductivity (µS /cm), numb er of droplets on the surface, and volume of water droplet (ml) are considered. The regression tree model is ob tained and the performance of the proposed system with other intelligence methods is compared. It can b e concluded that the performance of the least squares regression tree model outperforms the other intelligence methods, which gives the proposed model b etter generalization ab ility.