Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian

Abstract

Subsea Autonomous High Integrity Pressure Protection System is used in the subsea production process to lower the pressure level of downstream equipment and pipelines and to protect low-pressure pipelines and equipment. Once failure occurs, it will cause serious environmental damage and huge economic losses. In this article, a method of Dynamic Bayesian networks is proposed based on different failure types detected by different test methods. The reliability and availability of HIPPS with different detection methods were analyzed quantitatively. The results show that the performance of the system is improved significantly after inspection and maintenance. Compared with traditional methods, the performance of HIPPS is improved after the partial stroke test is introduced. Through sensitivity analysis, it is found that failure rates have a greater impact on the reliability of HIPPS valves. Increasing partial stroke test coverage can improve HIPPS performance. To improve the reliability of HIPPS, it is necessary to improve the reliability of the execution unit, especially the HIPPS valves. The analysis of the PST strategy can provide a theoretical basis for selecting the frequency of partial stroke test and functional test interval in actual projects.