|Table of Contents|

Probability matrix diagnosis algorithm based on PMC model(PDF)

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

Issue:
2017年04期
Page:
479-
Research Field:
Publishing date:

Info

Title:
Probability matrix diagnosis algorithm based on PMC model
Author(s):
Feng HailinLei HuaLiang Lun
School of Mathematics and Statistics,Xidian University,Xi’an 710126,China
Keywords:
system-level fault diagnosis probability matrix diagnosis algorithm absolute fault nodes aggregation nodes groups
PACS:
TP39
DOI:
10.14177/j.cnki.32-1397n.2017.41.04.013
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.

References:

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Last Update: 2017-08-31