[1]冯海林,雷 花,梁 伦.一种基于PMC模型下的概率性矩阵诊断算法[J].南京理工大学学报(自然科学版),2017,41(04):479.[doi:10.14177/j.cnki.32-1397n.2017.41.04.013]
 Feng Hailin,Lei Hua,Liang Lun.Probability matrix diagnosis algorithm based on PMC model[J].Journal of Nanjing University of Science and Technology,2017,41(04):479.[doi:10.14177/j.cnki.32-1397n.2017.41.04.013]
点击复制

一种基于PMC模型下的概率性矩阵诊断算法()
分享到:

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年04期
页码:
479
栏目:
出版日期:
2017-08-31

文章信息/Info

Title:
Probability matrix diagnosis algorithm based on PMC model
文章编号:
1005-9830(2017)04-0479-07
作者:
冯海林雷 花梁 伦
西安电子科技大学 数学与统计学院,陕西 西安 710126
Author(s):
Feng HailinLei HuaLiang Lun
School of Mathematics and Statistics,Xidian University,Xi’an 710126,China
关键词:
系统级故障诊断 概率性矩阵诊断算法 绝对故障基 节点集团
Keywords:
system-level fault diagnosis probability matrix diagnosis algorithm absolute fault nodes aggregation nodes groups
分类号:
TP39
DOI:
10.14177/j.cnki.32-1397n.2017.41.04.013
摘要:
系统级故障诊断是提高多处理器系统可靠性的必要手段。为了有效定位多处理系统中的故障单元,该文建立了一种基于PMC模型t可诊断条件下的概率性矩阵诊断算法。首先对一般概率性矩阵诊断算法进行仿真分析获悉其具有较高的误检率,在诊断过程中引进绝对故障基和节点集团思想,通过计算绝对故障基以寻找系统中的部分故障处理机,集团用于将不确定状态的节点单元分类以补充正常节点集合,改善了原诊断的限制条件。仿真实验验证:改进后的概率性矩阵诊断算法保持了很高的检测精度,并且随着节点数的增多极大地降低了误检率,提高了诊断效果,使得该算法具有广泛的适用性。
Abstract:
The system-level fault diagnosis,an efficient method,is an essential subject for the expanding multiprocessor system.In order to maintain the proper functioning of the system via locating or evading the fault nodes,the probability matrix diagnosis algorithm is studied under the PMC model in t diagnosable system.Firstly,according to the analysis result of the simulation experiments on the general probablility matrix diagnostic,the higher fault alarm rate is presented.The absolute fault nodes aggregation based on the syndrome matrix is introduced to identify some fault nodes,the nodes grouping is used to replenish the non-fault sets,and the rigorous condition is impaired.Finally,the modified probability matrix diagnosis algorithm is proposed to improve the diagnostic efficiency.Simulation experiments show that it keeps the superiority of high detection accuracy,reduces fault alarm rate with the nodes increasing,and confirms the impressive diagnostic efficiency and extensive application.

参考文献/References:

[1] Amagasaki M,Inoue K,Zhao Q,et al.Defect-robust FPGA architectures for intellectual property cores in system LSI[C]//Proceedings of 2013 the 23rd International Conference on Field Programmable Logic and Application(FPL).Porto,Portugal:IEEE,2013:1-7.
[2]Preparata F P,Metze G,Chien R T.On the connection assignment problem of diagnosable systems[J].IEEE Transactions on Electronic Computer,1967,16(12):848-854.
[3]Hakimi S L,Amin A T.Characterization of assignment of diagnosable system[J].IEEE Transactions on Computers,1974,23(1):86-88.
[4]宣恒农,张大方,张明.PMC故障模型的方程诊断[J].电子学报,2003,31(5):694-697.
Xuan Hengnong,Zhang Dafang,Zhang Ming.The equation diagnosis on PMC fault model[J].Acta Electronica Sinica,2003,31(5):694-697.
[5]宣恒农,韩忠愿,张大方.基于互测PMC模型的故障诊断方法及其应用[J].电子学报,2007,35(5):987-991.
Xuan Hengnong,Han Zhongyuan,Zhang Dafang.The fault diagnosis algorithm and its application about PMC model based on ex-test[J].Acta Electronica Sinica,2007,35(5):987-991.
[6]宣恒农,赵冬,苗春玲,等.基于PMC模型的MWOFD算法[J].计算机工程与应用,2017,53(3):226-230.
Xuan Hengnong,Zhao Dong,Miao Chunling,et al.MWOFD algorithm based on PMC model[J].Computer Engineering and Applications,2017,53(3):226-230.
[7]Falcon R,Almeida M.Nayak A.A binary particles swarm optimization approach to fault diagnosis in parallel and distributed systems[C]//Proceedings of 2010 IEEE Congress on Evolutionary Computation(CEC).Barcelona,Spain:IEEE,2010:1-8.
[8]Elhadef M.Solving the PMC-based system-level fault diagnosis problem using Hopfield neural networks[C]//Proceedings of 2011 IEEE International Conference on Advanced Information Networking and Application(AINA).Biopolis:Singapore:IEEE,2011:216-223.
[9]Srivastava H O,Gupta S C.Effect of fault patterns on systems level diagnosis of mesh networks[C]//Proceedings of 2013 the 10th International Conference on Wireless and Optical Communications Networks(WOCN).Bhopal,India:IEEE,2013:1-4.
[10]He Qiyu,Jing Qiu,Liu Ganjun,et al.System-level BITs fault diagnosis and isolation based on diagnostic tree and Bayesian network[J].Key Engineering Materials,2013(584):102-106.
[11]郭晨,梁家荣,冷明.基于PMC模型的条件故障诊断[J].电子学报,2015,43(11):2331-2337.
Guo Chen,Liang Jiarong,Leng Ming.The conditional fault diagnosis of PMC model[J].Acta Electronica Sinica,2015,43(11):2331-2337.
[12]陈蜀宇,陈四清,吕志华,等.基于局域网的系统级概率分布式故障诊断[J].计算机学报,2000,23(5):516-522.
Chen Shuyu,Chen Siqing,Lv Zhihua,et al.The system-level probabilistic distributed faulty diagnose based on local area network[J].Chinese Journal of Computers,2003,23(5):516-522.
[13]何涛,宣恒农.关于PMC模型故障诊断的算法研究[D].南京:南京财经大学信息工程学院,2010:5-23.
[14]郭晨,梁家荣,葛志辉,等.基于互测PMC模型的条件诊断算法[J].电子学报,2015,43(2):255-261.
Guo Chen,Liang Jiarong,Ge Zhihui,et al.A conditional diagnosis algorithm based on ex-test PMC model[J].Acta Electronica Sinica,2015,43(2):255-261.
[15]Zhang Dafang,Xie Gaogang,Min Yinghua.Node grouping in system-level fault diagnosis[J].Journal Computer Science & Technology,2001,16(5):474-479.
[16]Lai P L,Tan J M,Chang C P,et al.Conditional diagnosability measures for large multiprocessor systems[J].IEEE Transactions on Computers,2005,54(2):165-175.
[17]宣恒农,张瑞驰,何涛,等.PMC模型下的一个贪婪诊断算法.[J]计算机工程与科学,2015,37(8):1430-1435.
Xuan Hengnong,Zhang Ruichi,He Tao,et al.A greedy diagnosis algorithm for PMC model[J].Computer Engineering & Science,2015,37(8):1430-1435.

备注/Memo

备注/Memo:
收稿日期:2016-08-05 修回日期:2016-11-17基金项目:国家自然科学基金(71271165)
作者简介:冯海林(1966-),女,博士,教授,主要研究方向:系统可靠性预测,网络系统级故障诊断等,E-mail:hlfeng@xidian.edu.cn; 通讯作者:雷花(1989-),女,硕士,主要研究方向:网络级系统级故障、统计推断,E-mail:Huaerjiao@qq.com。
引文格式:冯海林,雷花,梁伦.一种基于PMC模型下的概率性矩阵诊断算法[J].南京理工大学学报,2017,41(4):479-485.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-08-31