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Estimation of parameters for the electrostatic discharge current equation with real human discharge events reference using genetic algorithms

机译:使用遗传算法估计具有实际人体放电事件参考的静电放电电流方程的参数

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Thorough study of the electrostatic discharge (ESD) current equation shows that it may be different from the equation proposed in the IEC 61000-4-2 Standard. This problem is dealt with in this paper. Using a 2.5 GHz digital oscilloscope and a 50 OMEGA Pellegrini target as the measuring system, and a dc power supply to provide a charging voltage of 2 kVdc, a series of measurements were performed, so real human-to-metal ESD current waveforms were recorded. Treating the average waveform as a reference, a genetic algorithm (GA) was applied to the equation of the IEC 61000-4-2 Standard for the ESD current, in order to achieve its best fitting to the data set. Four different error norms were used for the GA applications. The best result of the applications of each of them was saved and compared to the others. Thus, a very satisfactory modification of the Standard's equation is presented, which is closer to the real ESD current waveform.
机译:对静电放电(ESD)电流方程的深入研究表明,它可能与IEC 61000-4-2标准中提出的方程不同。本文将解决此问题。使用2.5 GHz数字示波器和50个OMEGA Pellegrini目标作为测量系统,并使用直流电源提供2 kVdc的充电电压,进行了一系列测量,因此记录了真实的人对金属ESD电流波形。将平均波形作为参考,针对ESD电流,将遗传算法(GA)应用于IEC 61000-4-2标准的方程,以使其最适合数据集。 GA应用程序使用了四种不同的错误准则。每个应用程序的最佳结果已保存下来,并与其他应用程序进行了比较。因此,提出了对标准方程的非常令人满意的修改,该修改更接近实际的ESD电流波形。

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