Probability of EMC Failure and Sensitivity Analysis With Regard to Uncertain Variables by Reliability Methods

In this study, we use a statistical approach to treat a risk analysis of an EMC default. This approach relies upon reliability methods from probabilistic engineering mechanics. An estimation of a probability of failure (i.e., probability that the induced current by crosstalk causes a malfunction of a device connected at the end of a cable) and a sensitivity analysis of this probability of failure is carried out by taking into account uncertainties on input parameters. The reliability methods introduced in this study allow to compute a probability of failure with a relative low computational cost compared to Monte Carlo simulation.

[1]  Robert E. Melchers,et al.  Radial Importance Sampling for Structural Reliability , 1990 .

[2]  Yan Zhang,et al.  Two Improved Algorithms for Reliability Analysis , 1995 .

[3]  Ralf Vick,et al.  Coupling of Stochastic Electromagnetic Fields to a Transmission Line in a Reverberation Chamber , 2011, IEEE Transactions on Electromagnetic Compatibility.

[4]  Probabilistic Study of the Coupling between Deterministic Electromagnetic Fields and a Stochastic Thin-Wire over a PEC Plane , 2007, 2007 International Conference on Electromagnetics in Advanced Applications.

[5]  Heyno Garbe,et al.  Combination of the failure probability with a random angle of incidence of the radiated interference , 2011, 2011 XXXth URSI General Assembly and Scientific Symposium.

[6]  R. Rackwitz,et al.  New light on first- and second-order reliability methods , 1987 .

[7]  Henrik O. Madsen,et al.  Structural Reliability Methods , 1996 .

[8]  Emmanuel Prouff,et al.  Modeling extreme values resulting from compromising electromagnetic emanations generated by an information system , 2014 .

[9]  K. Breitung Asymptotic approximations for multinormal integrals , 1984 .

[10]  A. Kiureghian,et al.  Second-Order Reliability Approximations , 1987 .

[11]  Geovany Araujo Borges,et al.  Efficient computation of stochastic electromagnetic problems using unscented transforms , 2008 .

[12]  J. Beck,et al.  Estimation of Small Failure Probabilities in High Dimensions by Subset Simulation , 2001 .