Vulnerability Assessment of a Multistate Component for IEMI Based on a Bayesian Method

Abstract

A method based on the Bayesian approach is proposed in this paper to assess the vulnerability of a multistate component when the available experimental data are insufficient. According to the proposed definition of hierarchical vulnerability distributions, each state probability function of components is represented by adjacent level distributions, and the restriction of vulnerability distributions is analyzed. Depending on the credibility interval of the parameters of vulnerability distributions, the joint prior probability density functions (PDFs) of these parameters can be obtained in different scenarios. Therefore, the joint posterior PDF of these parameters can be obtained by combining the joint prior PDF and the likelihood function based on a Bayesian formula. Then, the posterior probability function of each state can be obtained by the proposed method. In realistic situations, the estimation of the state probability functions will be more practical than single estimation of the state probability under a specific threat level of intentional electromagnetic interference (IEMI). The specific process of the method is presented, while the hierarchical vulnerability distributions are represented by lognormal cumulative distribution functions. Finally, a case study demonstrates the effectiveness of the proposed method.