基于粗糙集理论的内燃机气阀故障诊断研究  

Research on Fault Diagnosis of Diesel Engine's Air Valve Based on Rough Sets Theory

作　　者：张邦礼[1] 孙颖楷[1] 曹长修[1] 

机构地区：[1]重庆大学自动化学院,重庆400044

出　　处：《内燃机学报》2002年第2期153-156,共4页Transactions of Csice

基　　金：总参军训部国防预研基金;国家高等学校博士学科点专项基金 (980 61 1 1 7)

摘　　要：在内燃机神经网络故障诊断系统的基础上 ,引入粗糙集理论 ,对其在内燃机故障诊断特征参数属性优化中的运用进行了探索。利用可辨识矩阵算法对决策表进行属性约简 ,剔除其中不必要的属性 ,揭示了故障诊断条件属性内在的冗余性 ,降低了神经网络构成的复杂性。最后给出了属性约简的结果。On the basis of ANN fault diagnosis system of internal combustion engine,rough sets theory is introduced,and its application in characterized paramaters attribute optimization is explored too.The discernibility matrix algorithm is used to reduce attributes in decision table.The unnecessary attributes are eliminated.The inner redundancy of fault diagnosis systems condition attributes is revealed.And the complexity of neural networks structure is also decreased.The result of attribute reduction is given finally.

关 键 词：内燃机 气阀 故障诊断 粗糙集 人工神经网络 约简算法 

分 类 号：TK407[动力工程及工程热物理—动力机械及工程] TK413.62