Statistical Inference Model for Gas Discharge Tube Excited by Pulse Based on Poisson Process

Equipment at radio frequency front-end would be vulnerable excited by electromagnetic pulse. Consequently, the statistical inference model is needed for vulnerability assessment. Effect test is usually carried out to study the statistical characteristics of the equipment excited by pulse. Limited by experimental conditions, effect test cannot include pulses with different characteristics. In this article, a statistical inference model is proposed based on the ‘threshold’ effect test. The model considers the statistical characteristics of vulnerability is reflected by time delay of effect occurrence. Through derivation, the time delay obeys Weibull distribution and the scale parameter is related to the applied electromagnetic pulse. The model calculates the parameters based on two sets of test results and infers the statistical characteristics of time delay under pulses of other waveforms. Meanwhile, the latent variable is proposed and it is convenient to assess the vulnerability of equipment excited by pulse. The effect test for gas discharge tubes (GDTs) is carried out, the results are consistent with the statistical inference by the proposed model. The model can infer the vulnerability of equipment excited by waveforms of different amplitudes, based on two waveform effect test results.