摘要
研究了一种将有向图、模糊理论和遗传算法相结合的智能故障诊断方法。用有向图来构造系统模型,用模糊集来解决模型中的不确定性问题,用遗传算法来对可能的故障传播路径进行搜索。当被诊断的系统含有不可测量节点时,该方法仍然可以很好地进行诊断。将该方法应用于某大型导弹武器装备的故障诊断系统中,实践证明,该方法行之有效并可以大大提高故障诊断效率。
This paper studies a hybrid intelligent fault diagnosis method that integrates directed graph,fuzzy theory and genetic algorithm together.The directed graph is used to construct the model of the system,the fuzzy sets are used to handle uncertainty in the system modeled by directed graph,and genetic algorithm is used to search the possible fault-propagation paths.This method can also act well when the system having unmeasurable nodes.This method is used in the fault diagnosis system of a certain missile weapon system,and the result shows that this method is effective and can improve the efficiency of fault diagnosis.
出处
《计算机工程与应用》
CSCD
北大核心
2004年第9期212-215,共4页
Computer Engineering and Applications
基金
国家自然科学基金资助项目(编号:60272093)
关键词
智能故障诊断
遗传算法
模糊集
模糊有向图
导弹武器系统
Intelligent Fault Diagnosis,Genetic Algorithm,Fuzzy Sets,Fuzzy Directed Graph,Missile Weapon System
