Novel Fault Detection Optimization Algorithm for Single Event Effect system Based on Multi-information Entropy Fusion  

作　　者：高翔 周国昌 赖晓玲 张国霞 朱启 巨艇 

机构地区：[1]China Academy of Space Technology

出　　处：《Journal of Donghua University(English Edition)》2014年第6期879-881,885,共4页东华大学学报（英文版）

摘　　要：Fault detection caused by single event effect( SEE) in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.Fault detection caused by single event effect（ SEE） in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.

关 键 词：fault detection multi-information entropy posteriori information entropy correlation information matrix single event effect(SEE) 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]