一种融合差别矩阵和条件熵的故障诊断方法  

Approach for fault diagnosis of discernibility matrix and condition entropy fusion

作　　者：张光轶[1] 苏艳琴[1] 程继红[2] 

机构地区：[1]海军航空工程学院研究生管理大队,山东烟台264001 [2]海军航空工程学院科研部,山东烟台264001

出　　处：《计算机工程与应用》2011年第17期4-6,共3页Computer Engineering and Applications

基　　金：国家自然科学基金No.60802088~~

摘　　要：当约简对象过多时,粗糙集中基于差别矩阵的属性约简算法无法摆脱"知识爆炸"的问题。引入相对差别矩阵的概念,提出一种基于相对差别矩阵和条件信息熵的算法,比较分析了该算法与单纯应用差别矩阵算法和信息熵算法的优势,应用于某型机载电台设备进行故障诊断,结果表明3种算法结果一致,并且是对单纯差别矩阵和信息熵算法的简化。The reduction algorithm based on discernibility matrix algorithm can not avoid the ＂knowledge explosion＂ when the reduction objects are excessive.This paper introduces the relative disernibility matrix and proposes an algorithm based on relative discernibility matrix and condition entropy.Then the algorithm is applied to some aero radio equipment for fault diagnosis.The results show that the fault diagnosis results are consistent with those based on the pure discernibility matrix algorithm and pure condition entropy algorithm,and the new algorithm is simpler than the both two.

关 键 词：粗糙集 相对差别矩阵 条件信息熵 故障诊断 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] V24[自动化与计算机技术—控制科学与工程]