Name
Abstract | ||
|---|---|---|
An automated tester is built for IEC 61000-4-2 air discharges. The relations between the parameters of the resulting waveforms are studied using stochastic modeling. The precharge voltage, peak current and rise time are interrelated, with a strong dependence on the humidity. However, there is no clear dependence of the peak current and rise time on the approach speed. Naïve Bayes method is used to predict the peak current and rise time from the precharge voltage and humidity. The likelihood that a tablet experiences a soft failure is predicted via logistic regression. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IRPS.2018.8353548 | 2018 IEEE International Reliability Physics Symposium (IRPS) |
Keywords | Field | DocType |
System-level ESD,air discharge,stochastic modeling | Naive Bayes classifier,Electrostatic discharge,Voltage,Waveform,Rise time,Humidity,Electronic engineering,Mechanics,Engineering,Peak current | Conference |
ISSN | ISBN | Citations |
1541-7026 | 978-1-5386-5480-4 | 1 |
PageRank | References | Authors |
0.48 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Xiu | 1 | 1 | 0.82 |
| Samuel Sagan | 2 | 1 | 0.48 |
| Advika Battini | 3 | 1 | 0.48 |
| Xiao Ma | 4 | 252 | 34.88 |
| Maxim Raginsky | 5 | 771 | 60.65 |
| Elyse Rosenbaum | 6 | 61 | 21.99 |