Research on a Real-time Reliability Evaluation Method Integrated with Online Fault Diagnosis: Subsea All-electric Christmas Tree System as a Case Study

Abstract

The subsea all-electric Christmas tree is key equipment in subsea production systems. If a failure occurs, the marine environment will be seriously polluted. Therefore, strict reliability analysis and measures to improve reliability must be performed before such equipment is launched, which is crucial to safe subsea production. A real-time reliability evaluation method for the all-electric Christmas tree mechanical system integrated with the static Bayesian network fault diagnosis stage is proposed in this paper, which realizes the identification of the fault type of the components and the real-time reliability evaluation of the mechanical system under different failure rates of the components. As a supplement to the method, by using mutual information to conduct sensitivity analysis on the reliability of the mechanical system, the importance of the basic events of each component on the reliability of the system is finally given. The proposed method provides significant theoretical support for the maintenance of the subsea all-electric Christmas tree and can be extended to the reliability evaluation of general subsea production systems.

Air conditioning reliability analysis based on dynamic Bayesian network and Markov model

“…Bayesian Network (BN) is a probabilistic graph model that can effectively solve various uncertainty problems [6]. It has been introduced into the reliability analysis of complex systems and has achieved successful applications, such as subsea production systems [7][8][9], electronic systems [10,11], manufacturing systems [12][13][14], computer numerical control machine tools [15,16], wind turbines [17,18]. However, the traditional BN can only carry out static analysis, and it is difficult to model the transition process among multiple states.…”