4.7 Article

Using Bayesian networks in reliability evaluation for subsea blowout preventer control system

期刊

RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 108, 期 -, 页码 32-41

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2012.07.006

关键词

Bayesian networks; Reliability; Common cause failure; Imperfect coverage; Subsea blowout preventer

资金

  1. National High-Technology Research and Development Program of China [2007AA09A101]
  2. National Natural Science Foundation of China [50874115]
  3. Program for Changjiang Scholars and Innovative Research Team in University [IRT1086]
  4. Taishan Scholar Project of Shandong Province [TS20110823]
  5. Shandong Province Science and Technology Development Project [2011GHY11520]
  6. Incubation Programme of Excellent Doctoral Dissertation of China University of Petroleum [2010-02]

向作者/读者索取更多资源

The Bayesian network models of redundant systems including parallel system and voting system, taking account of common cause failure and imperfect coverage, are proposed. The Triple Modular Redundancy (TMR) and Double Dual Modular Redundancy (DDMR) control systems for subsea Blowout Preventer (BOP) are presented. By applying the proposed Bayesian network models, the reliability of subsea BOP control systems are evaluated at any given time, and the difference between posterior and prior probabilities of each single component given the system failure is obtained. The effects of coverage factor of redundant subsystem and failure rate of single component on reliability of systems are also researched. The results show that the DDMR control system has a little higher reliability than TMR system. To improve the reliability of subsea BOP control systems, the component failure rates of Ethernet switch (ES), programmable logic controller (PLC) and personal computer (PC) should be reduced for TMR system, whereas the failure rates of ES and PC should be reduced for DDMR system. The recovery mechanism of PLC, PC and ES subsystems, and PC and ES subsystems should be paid more attention for TMR and DDMR control systems, respectively. (C) 2012 Elsevier Ltd. All rights reserved.

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