基于多信号流图与分支定界算法的故障诊断

针对实时在线故障诊断问题,提出了一种基于多信号流图和分支定界算法的故障诊断方法。通过建立多信号流图模型生成相关矩阵作为诊断知识,进而由相关矩阵以及观测向量产生冲突集,使最小诊断集的求解过程映射为整数规划问题;采用分支定界算法,通过对冲突集的分支、定界以及剪支得到故障诊断的最优解,从而避免了穷举问题造成的搜索"爆炸"。以某型机载燃油系统为对象对本文提出的算法进行了验证。结果表明:本文算法与常用的多信号流图诊断推理算法TEAMS-RT相比,算法速度相当,故障定位精度更高,很好地涵盖单故障以及多故障组合,可以胜任大规模复杂系统的故障诊断。 

Research on fault diagnosis based on multi-signal flow graph and branch-and-bound algorithm

A complete fault diagnosis method based on multi-signal flow graph and branch-and-bound algorithm was proposed to deal with real-time online fault diagnosis problems. A multi-signal flow graph model was built for the object system and a dependency matrix was generated as diagnostic knowledge. Conflict sets was generated by the dependency matrix and the system observation vector, which was essential in transforming the problem of finding the minimal diagnosis set to a problem of integer programming. A new version of branch-and-bound algorithm was utilized to calculate the optimal solution of the diagnosis by branching, computing lower and upper bounds and pruning the conflict sets. In this way,explosion problem caused by enumeration could be avoided. By applying the proposed approach to a fuel system of aircraft, the efficiency of this method was verified. Diagnostic results by comparing with the existing TEAMS-RT algorithm demonstrate that the proposed method has a higher accuracy in locating the faults. Besides, both single-fault and multi-fault diagnostic problems can be covered and the method is capable of large-scale complex system fault diagnosis.