基于Markov和SFT的同类元件系统中元件维修率分布确定

为了扩展空间故障树SFT理论,研究可表示工作环境影响的元件维修率,借助Markov链理论对元件维修率分布进行推导。所研究系统的特点为由相同元件所构成,进而使Markov链中失效率和维修率相同。用SFT中的特征函数代替Markov链中失效率,并根据实际情况设定状态转移概率,从而可得SFT下的元件维修率分布。维修率分布是由工作环境因素作为自变量的函数。考虑工作时间t和工作温度c影响下,对一混联系统进行元件维修率分布计算。最终得到了元件维修率分布和正常状态转移概率范围,其具体计算要依赖于实例系统结构。最后论述了方法的不足及其原因。

Determine the component maintenance rate distribution in the system with similar components based on Markov and SFT

In order to expand the space fault tree SFT, and study component maintenance rate according to the environmental impact, component maintenance rate distribution are derived using Markov chain theory. The characteristics of studied system are by the same components, then make the same failure rate and repair rate of Markov chain. Substitute the SFT characteristic function of the failure rate in Markov chains, and set the state transition probability considering actual situation, and thus available components maintenance rate distribution. Repair rate distribution is a function by the work environment factors as the independent variables. Considering the influence of the working time t and temperature c, the component maintenance rate distribution of series-paralleling system is calculated. The hypothesis in the process, finally component repair rate distribution is obtained and the normal state transition probability range. This paper discusses the method disadvantages and the reasons.