论文部分内容阅读
为解决静电电位动态测量的补偿问题,提出了一种基于系统辨识的波形重建算法。设计了静电电位动态测量标准装置,对静电电位动态测量仪进行了校准实验,用数字存储示波器采集了标准高压方波输入信号及静电电位动态测量仪畸变输出信号,分别利用最小二乘法以及最优4阶辅助变量法,通过系统辨识得到了静电电位动态测量仪的时域传递函数模型,再用逆传递函数和静电电位动态测量仪实际输出信号恢复出原始被测静电电位信号,获得了满意的波形重建结果。实验结果验证了基于系统辨识波形重建算法的有效性,为提高静电电位动态测量的准确性提供了一种新手段。
In order to solve the problem of compensation of dynamic measurement of electrostatic potential, a waveform reconstruction algorithm based on system identification is proposed. The static electric potential dynamic measuring standard device was designed and the static electric potential dynamic measuring instrument was calibrated experiment. The digital high-pressure square wave input signal and electrostatic potential dynamic measuring instrument distortion output signal were collected by using the digital storage oscilloscope. The least square method and the optimal 4-order auxiliary variable method, the time-domain transfer function model of the electrostatic potential dynamic measuring instrument is obtained through system identification, and then the original measured electrostatic potential signal is recovered by using the inverse transfer function and the actual output signal of the electrostatic potential dynamic measuring instrument to obtain the satisfactory Waveform reconstruction results. The experimental results verify the effectiveness of the waveform reconstruction algorithm based on system identification and provide a new means to improve the accuracy of the dynamic measurement of electrostatic potential.