摘要
针对不协调信息条件下的航空发动机故障诊断问题,研究了基于信息熵属性约简的故障诊断方法。首先定义了故障诊断信息系统来描述不协调故障样本数据,针对基本粗糙集模型分类能力不足的问题,引入变精度粗糙集模型处理不协调诊断信息系统;然后针对现有条件熵不能区分不确定性规则的缺陷,提出了变精度条件熵作为属性重要度的度量标准,设计了启发式属性约简算法,提取故障诊断规则。将该方法用于航空发动机故障诊断,验证了该方法可有效处理不协调信息,显著提高了航空发动机故障诊断的准确率。
A diagnosis method is proposed to deal with the inconsistent information in aeroengine fault diagnosis based on information entropy attribute reduction. Firstly, a diagnosis information system is defined to describe incon sistent information. A variable precision rough set model is introduced to dispose the sample data set and improve the classification quality of base rough set. Then variable precision conditional entropy is proposed to serve as the meas urement of attribute significance and overcome the limitation of current conditional entropy in distinguishing uncertain rules. Based on the new attribute significance, a heuristic attribute reduction algorithm is designed to extract the di agnosis rules. This approach was used in the fault diagnosis of aeroengine. Results show that the developed ap proach can deal with inconsistent information effectively and enhance the diagnosis accuracy remarkably.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2012年第8期1773-1778,共6页
Chinese Journal of Scientific Instrument
基金
国防预研项目(51317030100)资助
关键词
故障诊断
变精度粗糙集
信息熵
属性约简
航空发动机
diagnosis
variable precision rough set
information entropy
attribute reduction
aero-engine
