利用马尔可夫更新理论，得到了系统的可用度，故障频度 和可靠度等各项指标。
Using Markov renewal theory we obtain some indexes such as the system availability, failure frequency and reliability function.
方法二针对状态空间巨大的情况，先以一定的标准对状态空间进行截尾，再应用马尔可夫模型获得系统的稳态可用度、首次故障前平均时间、稳态故障频度等可靠性指标。
The other first truncates the state space according to some criterion in view of the explosive number of states. Markov model is introduced to obtain some important reliability indexes.
为此，我们面向高频度故障，提出了一个基于原测试流程的局部优化方法，并且还提出了一个以减少诊断所需探针操作次数为目标的启发式故障诊断算法。
In this paper, a local-optimization method oriented to frequently occurring faults is presented. A heuristic fault diagnosis algorithm with fewer probing operations is also discussed.
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