The electronic control system assumes a crucial role in the management, regulation, and safeguarding of equipment within subsea production systems. To ensure the normal operation of the system and improve the reliability of the electronic control system, hardware redundancy is often employed. External shocks can accelerate the state transition of components, and the state changes of electronic control system components may affect other redundant components. Therefore, this paper proposes a multi-state competing failure reliability assessment method based on the correlation of redundant components. By analyzing the degradation and sudden failure processes of electronic control system components, a system state transition probability matrix based on Markov processes is constructed to delineate component state categorization and evolution. The hierarchical model is combined with dynamic Bayesian networks to quantify the impact of system redundancy component correlation on model parameters using a set of hyperparameters. Building upon this analysis, a hierarchical dynamic Bayesian network grounded in competing failure process is established. The probability of each component being in different states after undergoing a competing failure process is analyzed. After considering the influence of redundant component correlation, the overall system reliability deteriorates more rapidly. Finally, the system state evolution under different maintenance strategies is analyzed.
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