基于不同参数模型的安全计算机共因失效分数计算及比较分析
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摘要
采用常用的Beta参数模型计算联锁设备安全计算机的共因失效分数时,存在计算结果有偏差和不精确等问题。引入应用于核能领域的Alpha参数模型,证明并推导该模型获得的α因子与共因失效分数之间的等价关系。采用美国核管理委员会发布的安全计算机共因失效统计数据作为先验数据,计算获得2乘2取2及3取2这2种冗余结构的两阶和三阶α因子,根据等价关系得到共因失效分数。以这2种冗余结构为例,分别采用2种参数模型,计算系统平均危险侧失效概率P_(PFH)和由共因失效导致的危险侧失效概率。结果表明:共因失效导致的危险侧失效概率是P_(PFH)主要组成部分,α参数模型能够量化计算3重及以上冗余结构的共因失效分数,并获得更符合实际输出的P_(PFH)计算结果;同时,当共因失效数据不断完善时,α参数模型可以通过修正后验参数获得更准确的共因失效分数,为验证计算机安全完整性等级提供有利帮助。
Problems such as deviation and inaccuracy of the calculation results arise when using the commonly used Beta parameter model to calculate the common cause failure fraction of the safety computer based interlocking. The Alpha parameter model applied in the field of nuclear energy is introduced to prove and derive the equivalence relation between the α factor obtained by the model and the common cause failure fraction. Using the common cause failure statistics data of the safety computer issued by the US Nuclear Regulatory Commission as the prior distribution reference value, the second-order and third-order α factors of the two redundant structures of 2 oo3 and double 2 oo2 systems are calculated. According to the equivalence relation, a common cause failure fraction can be obtained. Taking these two kinds of redundant structures as examples, two kinds of parameter models are used to calculate the average frequency of dangerous failure for the system(P_(PFH)) and the frequency of dangerous failure caused by the common cause failure. Results show that the frequency of dangerous failure caused by the common cause failure is the main component of P_(PFH). The α parametric model can be used to quantify the common cause failure fraction of the three and above redundant structures and obtain the P_(PFH) calculation result which is more in line with the actual output. When the common cause failure data is continuously improved, a more accurate common cause failure fraction can be obtained through the α parameter model by correcting the posterior parameters, which is helpful for verifying the safety integrity level of the computer.
Problems such as deviation and inaccuracy of the calculation results arise when using the commonly used Beta parameter model to calculate the common cause failure fraction of the safety computer based interlocking. The Alpha parameter model applied in the field of nuclear energy is introduced to prove and derive the equivalence relation between the α factor obtained by the model and the common cause failure fraction. Using the common cause failure statistics data of the safety computer issued by the US Nuclear Regulatory Commission as the prior distribution reference value, the second-order and third-order α factors of the two redundant structures of 2 oo3 and double 2 oo2 systems are calculated. According to the equivalence relation, a common cause failure fraction can be obtained. Taking these two kinds of redundant structures as examples, two kinds of parameter models are used to calculate the average frequency of dangerous failure for the system(P_(PFH)) and the frequency of dangerous failure caused by the common cause failure. Results show that the frequency of dangerous failure caused by the common cause failure is the main component of P_(PFH). The α parametric model can be used to quantify the common cause failure fraction of the three and above redundant structures and obtain the P_(PFH) calculation result which is more in line with the actual output. When the common cause failure data is continuously improved, a more accurate common cause failure fraction can be obtained through the α parameter model by correcting the posterior parameters, which is helpful for verifying the safety integrity level of the computer.
引文
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[2] HAUGE S,HOKSTAD P,H?BREKKE S,et al.Common Cause Failures in Safety-Instrumented Systems:Using Field Experience from the Petroleum Industry[J].Reliability Engineering & System Safety,2016,151(7):34-45.
[3] ZUBAIR Muhammad,QAZI Muhammad Nouman Amjad.Calculation and Updating of Common Cause Failure Unavailability by Using Alpha Factor Model[J].Annals of Nuclear Energy,2016,90(4):106-114.
[4] REJC ?iva Bricman,EPIN Marko.An Extension of Multiple Greek Letter Method for Common Cause Failures Modelling[J].Journal of Loss Prevention in the Process Industries,2014,29(1):144-154.
[5] FLEMING Karl N,MOSLEH Ali,DEREMER R Kenneth.A Systematic Procedure for the Incorporation of Common Cause Events into Risk and Reliability Models[J].Nuclear Engineering and Design,1986,93(Supplement 2/3):245-273.
[6] TROFFAES M C M,WALTER G,KELLY D.A Robust Bayesian Approach to Modeling Epistemic Uncertainty in Common-Cause Failure Models[J].Reliability Engineering & System Safety,2014(125):13-21.
[7] 倪大江.民机安全性工作体系与共模故障分析方法研究[D].南京:南京航空航天大学,2007:46-47.(NI Dajiang.Research on Civil Airplane Safety Work System and Methods of Common Mode Analysis[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2007:46-47.in Chinese)
[8] 孔凡凡.民用飞机共模故障分析方法及工程应用研究[D].南京:南京航空航天大学民航学院,2008:37-42.(KONG Fanfan.Research on Common Mode Failure Analysis Method and Application for Civil Airplane[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2008:37-42.in Chinese)
[9] 程卓,遇今,郭泾平,等.航天器共因失效分析与预防初探[J].航天器工程,2010,19(6):121-125.(CHENG Zhuo,YU Jin,GUO Jingping,et al.Primary Study on Spacecraft Common Cause Failure and Preventive Actions[J].Spacecraft Engineering,2010,19(6):121-125.in Chinese)
[10] International Electrotechnical Commission.IEC 61508 Functional Safety of Electrical/Electronic/Programmable Electronic Safety-Related Systems[S].Geneva:International Electrotechnical Commission,2010:43-44.
[11] KANG D I,HWANG M J,HAN S H.Estimation of Common Cause Failure Parameters for Essential Service Water System Pump Using the CAFE-PSA[J].Progress in Nuclear Energy,2011,53(1):24-31.
[12] US Nuclear Regulatory Commission.NUREG/CR-5485.Guidelines on Modeling Common-Cause Failures in Probabilistic Risk Assessment[S].Washington:US Nuclear Regulatory Commission,1998:A-7-A-10.
[13] US Nuclear Regulatory Commission.CCF Parameter Estimations 2015[R].Washington:US Nuclear Regulatory Commission,2015:395-396.