关键词: 航空发动机;性能监控;故障检测;核主元分析法;主元分析法

Abstract: The aeroengine parameters possess some nonlinear features when the performance of aeroengine goes from normal to abnormal,and further from abnormal to completely faulty.In order to effectively detect the fault owned nonlinear feature,a novel approach of fault detection of aeroengine based on kernel principal component analysis(KPCA) model is presented.KPCA performs nonlinear transformation by kernel function to map the nonlinear input space into linear feature space and computes principal component by performing principal component analysis(PCA) in feature space,and detects faults by utilizing statistics T2 and SPE.The practical applications in monitoring certain type of turbine-fan engine show that KPCA is superior to PCA in fault detection and is more suitable to fault detection of aerogengine owned nonlinear feature.

Key words: Aeroengine;Performance monitoring;Fault detection;Kernel principal component analysis;Principal component analysis