PREDICTION CURRENT-VOLTAGE CHARACTERISTICS VARISTOR IN THE AREA LEAKAGE CURRENTS USING NEURAL NETWORKS
Prediction Current-voltage characteristics arrester leakage current in the area is necessary to solve the problem of the correct choice of networks with the presence of higher harmonic components at the design stage surge protection systems. The complexity of the problem of forecasting the Current-voltage characteristics varistor in the area leakage currents is that to construct adequate forecasting models must take into account not only the impact of stress and type of surge arresters, but a complex, non-linear behavior of the parameters of varistors, which depends on their composition and production technology.Therefore, the task of forecasting appropriate to use mathematical tools that would take into account nonlinear dependencies varistors parameters, such as neural networks. As input data used in the measurement results CVC varistors different voltage classes and different manufacturers. Based on analysis of the literature selected type of neural network, developed its structure and trained. The resulting neural network provides acceptable accuracy of the forecast current-voltage characteristics in the area of the leakage current.