基于贪婪算法的系统级故障的概率诊断

概率诊断算法是系统级故障诊断研究的一个重要方面,本文在集团理论的基础上,利用贪婪算法中不同贪婪准则提出了四个概率诊断算法.通过对诊断算法进行仿真,分析比较了各算法的性能,每种算法在较少的测试数情况下,均表现出较高的诊断正确率,且时间复杂度不高.四种贪婪算法中贪婪算法一的性能最优,实验结果表明,相对于经典的概率诊断算法—Compete算法与Majority算法,相同条件下,在诊断正确率上贪婪算法一要远好于Majority算法,在时间复杂度上要好于Compete算法,综合性能上要优于此两种概率诊断算法.

A Probabilistic Algorithm of System-Level Fault Diagnosis Based on Greedy Principle

Probabilistic diagnosis algorithm is very important in the system level fault diagnosis research.This paper proposes four probabilistic algorithms based on grouping theory and greedy principle for system-level fault diagnosis.By computer simulation,it is shown that these diagnosis algorithms can achieve a high probability of correctness under low time complexity.The greedy algorithm one has the best performance in the four probabilistic algorithms.The results also indicate that our algorithms have better performance than the Compete algorithm and Majority algorithm,which are classic probabilistic algorithms in system level fault diagnosis.