Reliability analysis of subsea pipeline system based on fuzzy polymorphic bayesian network

Subsea pipeline system faces significant challenges in practical engineering applications, including system complexity, environmental variability, and limited historical data. These factors complicate the accurate estimation of component failure rates, leading to fault polymorphism and inherent uncertainty. To address these challenges, this study proposes a reliability analysis method based on a Fuzzy Polymorphic Bayesian Network (FPBN). The approach utilizes a multi-state fault tree to construct a polymorphic Bayesian Network (BN), integrating traditional BN techniques with the consideration of multiple failure states and fuzzy failure rates. This extension allows the network to handle uncertainties such as imprecise fault data and unclear logical relationships. The method is applied to subsea pipeline risk analysis by developing a system BN model. Through quantitative analysis, the failure probability of the system is calculated. Reverse fault diagnosis is then conducted to determine the posterior probabilities of root nodes and identify system vulnerabilities. The results demonstrate that the FPBN effectively addresses the ambiguity and uncertainty in component failure rates, providing a robust framework with practical engineering applications.