Abstract: In order to discover the impact of atmospheric condition parameters on air gap discharge voltage,a auto- matic discharge monitoring device with ball-ball electrode was used to monitor and record the discharge voltage and atmospheric condition parameters in natural environment,and a calculation model of gray correlation was estab- lished,by which the gray correlations between atmospheric condition parameters and discharge voltage were ob- tained,finding that the gray correlations of atmospheric condition parameters are indicative of the following order: pressure ＞ temperature ＞ wind speed ＞ relative humidity ＞ illumination.Then,by taking the atmospheric condition parameters as inputs,Chebyshev neural network was used to predict the discharge voltage,with better prediction results being obtained in comparison with BP neural network.Finally,according to the sort of atmospheric condi- tion parameters,the first two ( pressure and temperature) ,the first three ( pressure,temperature and wind speed) and the first four ( pressure,temperature,wind speed and relative humidity) parameters were respectively taken as the inputs of Chebyshev neural network to predict the discharge voltage.The results show that,with the reduction of the number of inputs,the average relative error and maximum relative error of the predicted values both have little change.

Key words: atmospheric condition, air gap, discharge voltage, gray correlation, Chebyshev neural network