Predictions of the AC discharge voltage of short rod-plane air gap under rain conditions with the application of ANN

To obtain a mathematical model capable of predicting the breakdown voltage of air-gap in rain conditions, we adopted results gained in the artificial climate chamber to establish an artificial neural network (ANN) model of AC discharge voltage of rod-plane short air gap and breakdown voltage of air gap under rain conditions. With the help of this model, the AC discharge voltage of rod-plane short air gap under certain rain conditions can be forecasted, and the accuracy of prediction results is under the required range. Simultaneously, based on the ANN model, the effect of single and multiple factors on the breakdown voltage of air gap under rain conditions is simulated and analyzed, showing that, with the increment of rainfall intensity, rain conductivity and the decrement of ambient temperature, the breakdown voltage of air gap will reduce if the atmosphere pressure is constant; once varying one of the three factors, the impact that the other two factors exert on the breakdown voltage of air gap will change as well. Training data play an essential role in the prediction ability of ANN, which leads to an unaccepted error for the data out of the training range.