基于图论的通用测试性推理  

Graph Theory Based General-purpose Testability Inference

作　　者：王宝龙[1,2] 黄考利[1] 马立元[1] 连光耀[1] 

机构地区：[1]解放军军械工程学院,石家庄050003 [2]北京航天飞行控制中心,北京100094

出　　处：《弹箭与制导学报》2011年第6期207-210,共4页Journal of Projectiles,Rockets,Missiles and Guidance

摘　　要：为弥补传统测试性推理方法通用性差的缺陷,研究了基于图论的通用测试性推理技术,构建了一种通用测试性推理模型。其中,图论内核抽象了框图模型、信息流模型、多信号流图模型、混合诊断模型、贝叶斯网络模型和AI-ESTATE中的信息元素,融合了Floyd-Warshall算法、FDI算法和高阶关联关系推理算法,为测试性推理的通用化、标准化和并行化提供了一种新的解决方案。结合某装备测控系统的信号形成组合进行了推理方法验证,证明了方法的有效性和先进性。In order to make up the flaw of low universality of traditional testability inference methods,in the paper,a general purpose testability inference technology was given based on graph theory.A graph theory core was implemented to Abstract all testability information from frame model,information flow model,multi-signal flow model,hybrid diagnostic model,Bayesian model and artificial intelligence exchange and service related with all test environments（AI-ESTATE）,and melt general-purpose algorithms such as Floyd-Warshall algorithms,fault detection and isolation（FDI） algorithms and high order relation inference algorithms.It has provided a new solution to general-purpose,standard and concurrent testability inference for equipment.Graph theory based general-purpose testability inference technology is shown to be effective and advanced by the example of the testability inference for the certain equipment＇s signal generation unit.

关 键 词：测试性 图论 Floyd-Warshall算法 FDI 贝叶斯网络 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]