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Problem statement: The phenomenon of flashover in polluted insulators has been&#13; continued by the study of the characteristics of contaminating layers deposited on the surface of&#13; insulators in high voltage laboratories. In the literature, Experimental investigations have been carried&#13; out on a real insulator or a flat plate model of insulators under high voltage application. This study&#13; proposed the Equivalent insulator flat plate model for studying the flashover phenomena due to&#13; pollution under wet conditions even at low voltage. Laboratory based tests were carried out on the&#13; model under AC voltage at different pollution levels. Different concentrations of salt solution has been&#13; prepared using sodium chloride, Kaolin and distilled water representing the various contaminations.&#13; Leakage current during the experimental studies were measured for various polluted conditions.&#13; Approach: A new model of Vc = f (V, Iinitial, Iem, Iemax and I&#963;) based on artificial neural network has been&#13; developed to predict flashover from the analysis of leakage current. The input variable to the artificial&#13; neural network are mean (Imean), Maximum(Imax) and standard deviation(I&#963;) of leakage current extracted&#13; along with the initial value of leakage current Iinitial and the input voltage(V).The target obtained was used&#13; to evaluate the performance of the neural network model. Results: The optimum process has been carried&#13; out based on the training accuracy measured by RMSE, the network converged to a threshold of&#13; 0.0001.The trained model prediction is in good agreement with the actual results and the R2 value of the&#13; developed model is 0.99996. Conclusion: The developed ANN model is well-suited for the analysis of&#13; leakage current to predict flashover on the insulator surface with high accuracy

Analysis of Leakage Current to Predict Insulator Flashover Using Artificial Neural Network