摘要
提取发动机性能状态的特征参数,是提高发动机故障识别正确率和可靠性的必要条件.针对实际航空发动机故障参数所具有的模糊和连续性特点,提出了一种基于模糊粗糙集的特征参数提取算法,并应用到某型航空发动机故障识别.研究结果表明:属性约简的核则为导致发动机故障的特征参数,以此特征参数进行故障诊断,可保证较高的诊断精度;同时,该算法的抗干扰性提高了整个系统故障识别的正确率.该算法可用于航空发动机故障分类、故障诊断以及状态监控.
Extracting diagnostic parameters of aero-engine performance is an essential approach to enhance the validity and the reliability of aero-engine fault recognition. In view of fuzzy and consecutive characteristics of aero-engine fault parameters, an extracting algo-rithm based on fuzzy-rough sets was put forward and the algorithm was used for fault recog-nition of one aero-engine. The research result shows that the core attributes of reductions are diagnostic parameters of aero-engine failure, whereby the algorithm ensures high precision of fault diagnosis. The anti-interference ability of the algorithm enhances the validity of fault recognition. The algorithm can be also used for fault classification, fault diagnosis and per- formance monitoring of aero-engine.
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2008年第6期1127-1130,共4页
Journal of Aerospace Power
基金
天津自然基金(06YFJMJC01700)
关键词
航空
航天推进系统
模糊集
粗糙集
特征参数
故障识别
aerospace propulsion system
fuzzy sets
rough sets
diagnostic parameters
fault recognition
