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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

25

期数:

2015年05期

页码:

110-114

栏目:

安全与防范

出版日期:

2015-05-10

文章信息/Info

Title:

 A Dynamic Fault Diagnosis Algorithm Based on CBR

文章编号:

1673-629X（2015)05-0110-05

作者:

 冒志敏; 郑洪源; 丁秋林

 南京航空航天大学 计算机科学与技术学院

Author(s):

 MAO Zhi-min; ZHENG Hong-yuan; DING Qiu-lin

关键词:

 ; 动态故障集; 二分贝叶斯网络; 故障诊断; 先验故障概率

Keywords:

 ; dynamic fault set; bipartite Bayesian network; fault diagnosis; priori fault probability

分类号:

TP277

文献标志码:

A

摘要:

 针对单纯静态集的故障诊断算法存在诊断准确率低、效率差等缺点,文中提出了一种基于案例推理的动态故障集诊断算法( CBR-DFDA)。 CBR-DFDA算法根据故障与症状依赖的不确定性,采用二分贝叶斯网络建立依赖模型,在故障持续时间统计的基础上修正先验故障概率；并引入动态故障集,给出了故障案例的表示、案例属性约简、案例属性权重的分配及相似算法。实验结果表明,CBR-DFDA算法可以有效地针对动态故障集中的故障,改善内存的存储空间,提高诊断效率和准确率。

Abstract:

 For the shortcomings existing in the fault diagnosis algorithm of simple dynamic set,such as low efficiency and poor accuracy, propose a new algorithm to handle the fault diagnosis problem in the condition of dynamic fault set,called Dynamic Fault Diagnosis Algo-rithm based on Case-Based Reasoning ( CBR-DFDA for short) . Considering the uncertainty of dependency between failure and symp-toms,CBR-DFDA algorithm builds dependency model using bipartite Bayesian network,and corrects priori probability of failure on the basis of analyzing fault duration. Also,introduce a set of dynamic fault and give the way to express the failure,simplify the attributes and assign attribute weights in a specific case. Then the optimal solution will be gained through running the algorithm. Experimental results show that CBR-DFDA algorithm can improve utilization of the memory and obtain a higher diagnostic efficiency and accuracy for the failure in a dynamic fault set.

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更新日期/Last Update: 2015-07-09