基于粗糙集的装备故障诊断系统的算法研究

Algorithm Research on Equipment Fault Diagnosis System Based On Rough Set

通过设计基于粗糙集的装备故障诊断系统框架,以大屏幕投影系统的设备故障记录作为样本集,研究了粗糙集在装备故障诊断系统中的应用。针对数据预处理中缺失数据的填补问题,采用粗糙集理论和统计学理论相结合的方式,最大限度的保留了原始信息、产生规则的数量和可靠性;针对知识约简中规则生成速度慢等问题,采用了基于粒计算的粗糙集知识发现算法,将决策表中的属性集转换为二进制的矩阵对象,把复杂的知识约简转化为矩阵运算,降低了知识约简的时间复杂度,提高了生成规则运算效率,实现了故障诊断知识的快速自动获取。

By designing the prime frame of equipment fault diagnosis system and using equipment fault records of large screen system as a sample data,this article demonstrates and analyzes the application of Rough Set in the equipment fault diagnosis system.The following work has been done： by the method of combining the Rough Set theory with the Statistical theory,the datasets with missing values of records can be recovered;the algorithm of knowledge acquisition of Rough Set based on Granular Computing can be used to transform the attribute in decision sheet into matrix objects,then the complex knowledge simplification is transformed into matrix operation,thus the time consuming can be deducted,and the knowledge of fault diagnosis can be acquired automatically and more effectively.