Application of Bayesian Networks to Reliability Evaluation of Software System for Subsea Blowout Preventers

The work develops a redundant software system for subsea blowout preventers, including control logics, human-machine interface (HMI) programs, remote access and redundant databases in order to meet the high reliability requirement of subsea drilling. The Bayesian networks (BN) for control logics, HMI programs and redundant databases are built and then the whole BN are established. The quantitative reliability evaluation is performed by using Netica software. The probability of software failure is evaluated via forward analysis, and the posterior probability given the failure is evaluated via backward analysis. The mutual information is researched in order to assess the important degree of basic events. The results show that the probability of software failure is 0.04%, which can meet the requirement of subsea drilling. The triple common cause failure should be paid more attention in order to improve the software performance. In addition, the control logics have the most important influences on software safety; the HMI programs have the least important influences; and the redundant databases are in between.