期刊文献+

通信装备故障诊断贝叶斯网络 被引量:4

Fault-Diagnostic Bayesian Network of Communications Equipment
下载PDF
导出
摘要 为满足各通信部队对通信装备技术保障的要求,提出基于贝叶斯网络的故障诊断方法。分析贝叶斯网络在通信装备故障诊断方面的优势,以某型通信装备的某故障为例,研究了通信装备故障诊断贝叶斯网络的建模、参数设置、推理等关键技术。基于NETICA软件演示了基于贝叶斯网络的通信装备故障诊断的一般过程,验证了贝叶斯网络在通信装备故障诊断中应用的可行性与有效性。 To satisfy the request of communications equipment technical support of communications troops,put forward the faulty diagnostic methods based on Bayesian Network.After analysis the advantages of Bayesian network in the aspect of fault diagnosis of communication equipment,taking certain fault of certain communications equipment as an example,research these key technology,including: the modeling of Fault-diagnosis Bayesian Networks of communication equipment,parameter setting and reasoning,etc.This paper utilizes the software of NETICA to demonstrate the common process of diagnostic methods of fault based on Bayesian network,verifies the feasibility and validity of the applying Bayesian network in the faulty diagnostic methods of the communication equipment.
出处 《兵工自动化》 2011年第7期79-81,85,共4页 Ordnance Industry Automation
关键词 通信装备 故障诊断 贝叶斯网络 communications equipment fault diagnose Bayesian network
  • 相关文献

参考文献11

二级参考文献89

  • 1张宏辉,唐锡宽.贝叶斯推理网络在大型旋转机械故障诊断中的应用[J].机械科学与技术(江苏),1996,25(2):43-46. 被引量:12
  • 2宫义山,赵海,哈铁军,张永庆,徐峰.多源信息的模糊决策树融合算法研究[J].沈阳工业大学学报,2006,28(2):127-131. 被引量:3
  • 3史志富,张安,何胜强.基于贝叶斯网络的多传感器目标识别算法研究[J].传感技术学报,2007,20(4):921-924. 被引量:20
  • 4Zhang N L, Poole D. A simple approach to Bayesian network computations[C].Proceedings of the Tenth Canadian Con ference on Artifieial Intelligence, 1994 : 171 - 178. 被引量:1
  • 5Dechter R. Bucket elimination: a unifying framework for probabilistic inference[C].Proceedings of the Twelthth Confer ence on Uncertainty in Artificial Intelligence, Portland, Oregon, 1996: 211-219. 被引量:1
  • 6Kask K, Dechter R, Larrosa J, et al. Bucket-tree elimination for automated reasoning [J]. Artificial Intelligence, 2001 (125): 91-131. 被引量:1
  • 7Zhang N L, Poole D. Exploiting causal independence in Bayesian network inference[J]. Journal of Artificial Intelligence Research, 1996(5) : 301 - 328. 被引量:1
  • 8Amestoy P R, Davis T A, Du I S. An approximate minimum degree ordering algorithm[J]. AIAM Journal of Matrix Analysis and Aplications, 1996, 17(4) : 886 - 905. 被引量:1
  • 9Shachter R. Evidence absorption and propagation through evidence reversals [J]. Uncertainty in Artificial Intelligence, 1990(5): 173 - 190. 被引量:1
  • 10Adrian Y W C, Boutilier C. Structured Arc Reversal and Simulation of Dynamic Probabilistic Networks[C].Proceedings of the Thirteenth ConJerence on Uncertainty in AI (UAI-97), 1997. 被引量:1

共引文献76

同被引文献24

引证文献4

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部