Feature extraction based on rough kernel Fisher discriminant analysis and its application on aeroengine fault diagnosis

A new approach based on rough kernel fisher discriminant analysis(RKFDA) was proposed for aeroengine fault feature extraction,which combined rough set and kernel Fisher discriminant analysis.Firstly,rough set was used to exclude the features irrelevant to the fault;reduce the dimension of features,remove the effect of disturbance characteristics and cut down the cost of computation.Secondly,kernel Fisher discriminant analysis was employed on the obtained subset of features to extract the nonlinear features.Finally,fault extraction and recognition experiments in aeroengine lubricating oil system were carried out to test the performance of this method.The results show that the extracted features based on the proposed method could improve the recognition for aeroengine fault,and reduce efficiently the dimension of features with strong adaptability and robustness for various classifiers.