摘要
结合粗糙集理论和灰色系统理论对不精确信息处理的优势,文中提出一种融合粗糙集理论与GM(1,1)灰色预测模型的故障预测方法,先运用粗糙集的属性约简算法对故障诊断决策表进行约简,推出最优诊断规则,再利用GM(1,1)灰色预测模型对约简决策表中的各条件属性测试值计算得到其预测值,从而代回约简的诊断决策表进行故障预测,最后在某型机载电台装备中以某一故障为例进行应用验证,结果表明故障预测效率和精度都较高,从而为提高装备的可靠性和维修性提供依据。
Rough Sets Theory and Grey System Theory both have the same advantage of processing inaccuracy data,so a fusion algorithm based on Rough Sets Theory and GM（1,1）Grey prediction model is proposed.The attribute reduction algorithm of Rough Sets Theory reduces the fault diagnosis decision table,and the optimal diagnosis rules are deduced.Then,GM（1,1）calculates the condition attributes predicted value of reduced decision table by their test value,which substitutes back to the reduction diagnosis decision table for fault prediction.It is verified in one fault of some aero radio equipment,and the results indicate that the efficiency and accuracy of fault prediction are both quite higher,which provides the foundation to improve the equipment reliability and maintainability.
出处
《计算机测量与控制》
CSCD
北大核心
2012年第2期291-293,306,共4页
Computer Measurement &Control
基金
国家自然科学基金资助项目(60802088)
关键词
灰色系统理论
粗糙集理论
融合
故障预测
grey system theory
rough sets theory
fusion
fault prediction
