Reliability Evaluation Methodology of Complex Systems Based on Dynamic Object-Oriented Bayesian Networks

A novel reliability evaluation methodology of complex systems is proposed using dynamic object-oriented Bayesian networks (DOOBNs). This modeling methodology consists of two main phases, namely, construction phases for object-oriented Bayesian networks (OOBNs) and for DOOBNs. In the first phase, the network fragments with similar structures and parameters are divided into classes; these classes are then encapsulated. The construction of OOBNs is completed according to the relationship among the encapsulated classes. In the second phase, every fragment of the dynamic Bayesian networks that was constructed by the first phase is encapsulated as a class called DOOBN. The construction of DOOBNs is completed according to the relationship among the time fragments. The accuracy of this methodology is validated using the all-series, all-voting, voting-after-series, series-after-voting, parallel-after-series, and series-after-parallel systems. This methodology is further illustrated and verified by using deepwater blowout preventer system and can model the system from global to local levels, thereby effectively reducing modeling difficulty and adopting efficient arithmetic reasoning algorithms.