Concurrent fault diagnosis method for electric-hydraulic system: Subsea blowout preventer system as a case study

Electric-hydraulic control system is widely used in subsea oil and gas drilling and production equipment because of its excellent performance. Efficient fault diagnosis of electrical control system helps improve economic benefits and safety of operators. The multi-component characteristics of electro-hydraulic control system make concurrent fault diagnosis a challenging problem. A model-driven method using the Bayesian network and D-S evidence theory is proposed in this paper to diagnose concurrent faults of the electro-hydraulic control system. The electro-hydraulic control system diagnosis problem is divided into multiple fault diagnostic sub-models based on the analysis of system structure and work process. A sub-model is established based on OOBNs for preliminary diagnosis and reasoning. The concurrent fault diagnosis and reasoning model is established based on the D-S evidence theory. The evaluated fault probability and diagnostic belief degree of each fault are combined. Fault identification rules combined with fault probability and diagnostic belief are established. A control system for a subsea blowout preventer is used as a case to demonstrate the proposed method.