基于神经网络电极移动速度影响放电参数分析

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

结合小间隙放电的双过程模型[1],探讨电极移动引起的气体压强变化和场强变化对放电间隙内部相关因子的影响[2],进而分析电极移动速度对放电参数的影响.基于静电放电电极移动速度效应检测仪,不断改变电极移动速度,反复多次进行放电实验,统计试验数据,然后利用神经网络进行仿真分析,探究电极移动速度与放电参数之间的相关性.结果表明:电极移动速度与放电电流峰值、平均上升速度之间具有正的线性相关性,与平均下降速度间具有负的线性相关性.研究结果对于探寻非接触式静电放电的规律和静电放电标准的制定,有一定的参考价值.

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.