图论模型与算法在航天器下行数据故障诊断知识循环依赖缺陷检测中的应用  

Application of Graph Theoretic Model and Algorithm in Circular Dependency Knowledge Defect Detection of Spacecraft Downlink Data Fault Diagnosis System

作　　者：王蕊[1,2] 沈星 吴伟[3] 潘顺良[3] WANG Rui;SHEN Xing;WU Wei;PAN Shunliang(College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Beijing Orient Institute of Measurement and Test,Beijing 100094,China;Beijing Institute of Spacecraft System Engineering,Beijing 100094,China)

机构地区：[1]南京航空航天大学航空学院,南京210016 [2]北京东方计量测试研究所,北京100094 [3]北京空间飞行器总体设计部,北京100094

出　　处：《载人航天》2023年第2期258-263,共6页Manned Spaceflight

摘　　要：针对中国空间站等航天器下行数据故障诊断系统中循环依赖的诊断知识缺陷,通过引入图论模型,将诊断知识中的循环依赖检测问题抽象为有向图中的环搜索问题,应用经典拓扑排序算法、Kosaraju算法和Tarjan算法开展诊断知识的缺陷检测,并结合诊断知识经常迭代更新的特点,提出了一种改进Tarjan算法。仿真结果表明:改进Tarjan算法比Tarjan算法能节省更多的计算开销。ed into a cycle search problem in a directed graph.Thus the classic topological sorting algorithm,Kosaraju algorithm,and Tarjan algorithm could be used to carry out defect detection of the diagnostic knowledge.Considering the characteristics of iterative updates of the diagnostic knowledge,an improved Tarjan algorithm was proposed.The simulation results showed that the improved algorithm could save more computational cost than simply using the Tarjan algorithm.

关 键 词：航天器 故障诊断 循环依赖知识缺陷 图论 改进Tarjan算法 

分 类 号：V557.3[航空宇航科学与技术—人机与环境工程]