A fault diagnosis method for the HIPPS of FPSO unit based on dynamic Bayesian network

Abstract

The high integrity pressure protection system (HIPPS) on the Floating Production Storage and Offloading (FPSO) unit is essential for handling various emergencies. However, if the location of the fault cannot be accurately identified, proper measures may not be taken to isolate the hazard. This paper presents a fault diagnosis method for HIPPS on FPSO units based on Dynamic Bayesian network (DBN). The method considers the influence of sensor and system equipment degradation on the diagnosis results and avoids the problem of overdiagnosis in static diagnosis networks. Six fault diagnosis cases of the system are analyzed and discussed to verify the accuracy and effectiveness of the proposed method. By changing the failure rate of the faulty component, it is determined that the posterior probability of the faulty component increases with the increase of the failure rate at the same time.