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Cascading failure assessment of complex systems based on Bayesian networks

机译:基于贝叶斯网络的复杂系统级联故障评估

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A cascading failure assessment method based on Bayesian network (BN) is proposed in order to improve the reliability of complex system and show cascading failure longitudinal relationship among system, subsystems and components. The probability index of cascading failure is given by using conditional probability of BN which is transformed from fault tree (FT). After that, junction tree inference algorithm is adopted here to carry out bidirectional reasoning to exhibit quantitative assessment of influence on system failure due to subsystem or component failure and possibility of component failure under the condition of system failure. Finally, the method is applied to cascading failure assessment of 2-bus automatic alarm subsystem in ship wet sprinkler system to demonstrate its effectiveness.
机译:为了提高复杂系统的可靠性,并显示系统,子系统和组件之间的级联故障纵向关系,提出了一种基于贝叶斯网络的级联故障评估方法。级联故障的概率指标是使用从故障树(FT)转换而来的BN条件概率给出的。此后,此处采用联结树推理算法进行双向推理,以定量评估对子系统或组件故障对系统故障的影响以及系统故障情况下组件故障的可能性。最后,将该方法应用于船舶湿式喷水灭火系统中的2总线自动报警子系统的级联故障评估中,证明了该方法的有效性。

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