基于Bayes和FTA的机床故障推理研究（英文）

Research on the inference of CNC machine fault based on Bayes and FTA

由于机床故障树的复杂性,通过对故障树进行模块化分解得到具有相似模块结构的子模块,并建立模块库进行存储。介绍了基于模块库的对故障特征进行检索的基本流程和原则,同时为了避免重复检索以及NP问题的产生,引入了有效模块的概念,即在遍历模块库时,不仅要考虑事件在故障树中上下层级关系,也要考虑各事件之间的从属关系。最后研究了一种基于贝叶斯理论的重要度最优排序方法并进行重要度校正。核心是引入了有效模块的概念和对最小割集进行基于贝叶斯理论的重要度最优排序。结果表明:该方法能有效缩短求解规模,诊断速度快,重要度排序可信度高。

Due to the complexity of the fault tree,the fault tree will firstly be decomposed to obtain sub-modules with similar modular structure,and also the module library will be built to store the sub-modules. This paper will introduce the basic processes and principles of feature-retrieval based on module library. In order to avoid repetition retrieval and NP problem,the concept of valid module will be introduced,that is to not only consider the hierarchy relationship of the event in fault tree,but also consider the affiliation between each event when traversing module library.Finally,this paper studies an optimal sorting method of importance based on Bayesian theory and also makes the importance correction. The core component of this paper is to build the module library based on the basic modular structure,and also introduce the concept of valid module as well as optimal sorting of importance based on Bayesian theory on the minimum cut sets. The present study result indicates that this method can effectively reduce the solving size,accelerate the speed of diagnosis,and improve the credibility of importance sorting as well.