考虑多故障的测试性建模改进方法

石君友; 龚晶晶; 徐庆波

考虑多故障的测试性建模改进方法

北京航空航天大学工程系统工程系, 北京 100191

详细信息

作者简介:
石君友(1973-),男,黑龙江齐齐哈尔人,高级工程师,shijy016@sina.com.

中图分类号: TP 301.6
计量
- 文章访问数: 3722
- HTML全文浏览量: 194
- PDF下载量: 1402
- 被引次数: 0
出版历程
- 收稿日期: 2009-02-26
- 网络出版日期: 2010-03-31

Improvement method for testability modeling with multiple faults

Dept. of System Engineering of Engineering Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

摘要

摘要: 分析了测试性建模的现有方法及在工程应用中存在的不足.在信号流图方法的基础上,提出了一种测试性建模的改进方法.该方法支持单元的多故障模式设置,能够区分全局故障和局部故障,并允许设置全局故障沿单元特定信号流方向传递.给出了测试性模型的图形定义、隐含属性定义、相关性矩阵定义和相应的测试性分析推理方法.在此基础上,提出了基于高阶相关性分析的相关性矩阵生成改进算法.以某惯导系统为例进行了应用,建立了测试性图形模型并生成改进的相关性矩阵,与现有方法建立的相关性矩阵进行对比,结果验证了测试性建模改进方法的可行性和有效性.
- 建模 /
- 故障检测 /
- 算法 /
- 信号流图 /
- 相关性矩阵
Abstract: The existing methods for testability modeling were analyzed,and their shortcomings in project application were given. An improvement method for testability modeling was proposed, based on the signal flow graph method. It supports to set multiple faults for units, and can distinguish between global fault and local fault, while the global fault can be set to propagate along special signal flow of units. The graph definition, the hide attributions definition, the dependency matrix definition of the testability model and the corresponding testability inference method were provided. An improvement algorithm to generate the dependency matrix was presented, based on the high order dependency analysis. An inertial navigation system was taken as an example for modeling. The system testability graph model was built. The improving dependency matrix was generated, and compared with the dependence matrix built with the exiting method. The result shows the feasibility and validity of the improvement method for testability modeling.
- model buildings /
- fault detection /
- algorithms /
- signal flow graph /
- dependency matrix

HTML全文

参考文献(1)

[1] 薛凯旋,黄考利,张玮昕,等.基于多信号模型的测试性分析与故障诊断策略设计[J].弹箭与制导学报,2008,28(4):225-227 Xue Kaixuan,Huang Kaoli,Zhang Weixi,et al.Testability analysis and fault diagnosis strategy design based on multi-signal model[J].Journal of Projectiles,Rockets,Missiles and Guidance,2008,28(4):225-227(in Chinese) [2] 连光耀,黄考利,吕晓明,等.基于混合诊断的测试性建模与分析[J].计算机测量与控制,2008,16(5):601-603 Lian Guangyao,Huang Kaoli,Lv Xiaoming,et al.Analyzing and modeling of testability based on hybrid diagnostic[J].Computer Measurement & Control,2008,16(5):601-603(in Chinese) [3] Eric Gould.Modeling it both ways:hybrid diagnostic modeling and its application to hierarchical system designs //Autotestcon 2004 Proceedings.San Antonio: Institute of Electrical and Electronics Engineers,2004:576-582 [4] 田仲,石君友.系统测试性设计分析与验证[M].北京:北京航空航天大学出版社,2003:171-213 Tian Zhong,Shi Junyou.System testability design analysis and demonstration[M].Beijing: Beijing University of Aeronautics and Astronautics Press,2003:171-213(in Chinese) [5] 龚勇,景小宁,陈云翔,等.基于多信号流图的飞控系统实时故障诊断[J].电光与控制,2006,13(6):89-92 Gong Yong,Jing Xiaoning,Chen Yunxiang,et al.Real-time fault diagnosis for flight control system based on multi-signal flow graph[J].Electronics Optics & Control,2006,13(6):89-92(in Chinese) [6] 龙兵,王日新,姜兴渭.多信号模型航天器配电系统最优测试技术[J].哈尔滨工业大学学报,2005,37(4):440-443 Long Bing,Wang Rixin,Jiang Xingwei.Optimal test technology for distribution systems of spacecrafts based on multi-signal model[J].Journal of Harbin Institute of Technology,2005,37(4):440-443(in Chinese) [7] 赵建军,梁翔宇,张小枫,等.基于多信号模型的武器装备故障诊断系统设计[J].电子测量技术,2008,31(11):103-107 Zhao Jianjun,Liang Xiangyu,Zhang Xiaofeng,et al.Design of test system for the weapon system based on the multi-signal modeling methodology[J].Electronic Measurement Technology,2008,31(11):103-107(in Chinese) [8] Guo Li,Jianmin Gao,Fumin Chen,et al.A new approach for construction of diagnostic Bayesian network //Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery.Washington:IEEE Compute Society,2007:647-652 [9] Lucas P J.Bayesian model-based diagnosis[J].Int J Approx Reason,2001,27(2):99-119 [10]  Luo Jianhui,Tu Haiying,Pattipati Krishna,et al.Diagnosis knowledge representation and inference[J].IEEE Instrumentation and Measurement Magazine,2006,9(4):45-52

施引文献

资源附件(0)

访问统计