Evaluating the Hazardous Failure Rate of majority voting computer architectures by means of Bayesian Network models

Safety-critical control systems are usually based on majority voters. In order to assess the compliance of these architectures with international safety standards, the probability of the occurrence of unsafe events should be evaluated by developing and analyzing proper formal models. In this paper we demonstrate that a Bayesian Network (BN) model can be used to evaluate the Mean Time Between Hazardous Events (MTBHE) of voting architectures. The proposed modeling approach is applied to a “2 out of 2” (2oo2) voter consisting of independent computing units. The results obtained from the analysis of the BN model of the 2oo2 voter can be easily extended to evaluate the hazardous failure rate of more complex voting architectures (e.g. Triple Modular Redundant architectures, based on a 2oo3 voting).