Aeroengine Rub-Impact Fault Diagnosis Based on Wavelet Packet Transform and the Local Discriminate Bases

Abstract

With the development of aeroengine towards the direction of high speed and high performance, the clearance between rotor and stator in aerongine is reduced so that the possibility of rub-impact fault is increased. Since rub-impact signals often exhibits non-stationarity, an integrated approach, which combines the wavelet packet transform (WPT) with local discriminate bases (LDB), is presented in this study to diagnose the rub-impact faults. Specifically, the LDB algorithm is used to select an optimal set of orthogonal time-frequency subspaces resulted from WPT, which have the best discriminatory information for aeroengine rub-impact fault classification. Then the desired parameters generated by the LDB vectors were taken as input to a Bayes classifier for identifying rub-impact faults. Experimental results from the aeroengine vibration signals show that the fault diagnosis method can classify working conditions and fault patterns effectively.