基于信息熵的最少测试费用故障诊断策略

Information entropy-based fault diagnosis strategy with least test cost

针对大系统顺序故障诊断中的测试排序问题,介绍一种基于信息熵的最少测试费用诊断树产生算法,这种算法比传统算法计算量少,又可有效利用测试结果、测试费用和故障概率等信息,该算法适合于在线和离线诊断维修过程。给出了算法的设计过程,并以实例说明算法的有效性。

Directed towards the test sequencing problem in the sequential fault diagnosis for large scale systems, an algorithm based on information entropy for design the fault diagnosis strategy with least test cost was presented. The algorithm requires less computation than the traditional methods, and uses the test results, test cost, and fault probabilities efficiently. This algorithm is suitable for on-line or off-line diagnosis and maintenance process. The design process of the algorithm was presented, and an example was used to illustrate the validity of the method.