Electrostatic discharge parameters affected by velocity of electrodes based on neural network

Combining the two-process model of small gap discharge, we discuss the influence of electrode pressure and the change of the field intensity on the internal factors of the discharge gap, and then analyze the influence of the electrode moving speed on the discharge parameters. Based on the electrostatic discharge effect tester independently developed by our team, repeated experiments are performed at different electrode moving speed, and the obtained data are utilized to use nerves. The network performs simulation analysis and explores the correlation between the electrode movement speed and discharge parameters. The final result shows that there is a positive linear correlation between the speed of movement of the electrode and the peak value of the discharge current and the average rate of rise, and a negative linear correlation with the average rate of decline. The research results have certain reference value for studying the rules of non-contact electrostatic discharge.