大型复杂系统故障隔离智能优化策略  

Large-scale Complex System Fault Isolation Intelligent Optimal Strategy

作　　者：蒋荣华[1] 王厚军[1] 龙兵[1] 

机构地区：[1]电子科技大学自动化学院,成都610054

出　　处：《系统仿真学报》2009年第3期841-844,共4页Journal of System Simulation

基　　金：国防基础科研项目(A1420061264);自然科学基金(60673011)

摘　　要：大型复杂系统的故障隔离是系统维修的重要环节,现有的故障隔离算法存在平均故障隔离时间(MFIT)长,不能快速自动生成决策树等缺点。利用AO*算法自动构造决策树,将离散粒子群算法应用于AO*算法的每一个节点的测试选择,降低计算复杂度,使故障隔离策略智能化。实例表明:该算法将故障隔离时间缩短20%,并降低测试代价,提高故障隔离效率,为大型复杂系统故障隔离提供一种高效算法。Fault isolation （F1） of Large-scale complex system is an important part of system maintenance. Long mean fault isolation time （MFIT） and being incapable of quickly automatic building of FI decision-making tree are the disadvantages of existing methods. The AO＊ algorithm builds the decision-making tree automatically; discrete binary particle swarm optimization algorithm applied to the test node selection reduces the complexity and intelligent FI strategy. The example validates that this algorithm has shortened 20% MFIT, decreased the test cost and improved the efficiency of FI. It offers an efficiency algorithm to the fault isolation of large-scale complex system.

关 键 词：故障隔离 平均故障隔离时间 离散粒子群算法 AO＊ 

分 类 号：TP306.2[自动化与计算机技术—计算机系统结构]