Reliability assessment of urban rail transit vehicle on-board controller with multi-component failure dependence based on R-vine-copula

The reliability of the vehicle on-board controller (VOBC) is crucial for ensuring the stable and safe operation of urban rail transit trains. To address the reliability assessment challenge with multi-component failure dependence under small sample conditions, this study proposes a method based on uncertainty distribution and the R-vine copula model. The method consists of three steps. First, the uncertainty distribution is employed to accurately describe the marginal distributions of each component. Second, an R-vine copula model is constructed to capture the dependencies among multiple component failures, leading to the derivation of an analytical solution for the reliability of the VOBC system. Finally, to tackle the estimation of unknown parameters in the reliability model, a two-stage statistical inference method is developed, incorporating the Particle Swarm Optimization Least Squares (PSO-LS) algorithm and the Sequential Estimation (SE) method. To demonstrate and validate this approach, this paper presents a simulation case as well as two practical cases from the Beijing subway Line 7 and Changping Line. The results indicate that the method exhibits superiority, with accuracy comparable to that of the simulation method.