Title :
Fault diagnosis of rotor rub based on ensemble EMD
Author :
Yu, Yang ; Lang, Huihui
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang, China
Abstract :
The fault signal of rotor rub is a typical nonlinear and non-stationary data. HHT is considered an effective method on that kind signal and the crucial step is EMD. However, one of the major drawbacks of the EMD method is mode mixing. Ensemble Empirical Mode Decomposition (EEMD) has been proposed recently. This method overcomes the mode mixing and represents a major improvement of the EMD method. The essence of EEMD is simple: by sifting an ensemble of white noise-added signal, treating the means as the final result. Local rotor rub fault signal was simulated by the rotor test rig in the paper. Compared with IMFs decomposed by EMD and EEMD individually, and then illustrated the EEMD has a better result. Finally, the time-frequency spectrum and marginal spectrum gained by means of Hilbert Transformation illustrated the EEMD is an effective method for fault diagnosis of rotor rub.
Keywords :
Hilbert transforms; acoustic signal processing; fault diagnosis; rotors; sliding friction; time-frequency analysis; Hilbert Transformation; ensemble empirical mode decomposition; fault diagnosis; local rotor rub fault signal; marginal spectrum; rotor rub fault signal; time-frequency spectrum; white noise-added signal ensemble; Accidents; Data analysis; Data engineering; Fault diagnosis; Information science; Instruments; Shafts; Stators; Testing; White noise; EEMD; EMD; fault diagnosis; rotor rub;
Conference_Titel :
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3863-1
Electronic_ISBN :
978-1-4244-3864-8
DOI :
10.1109/ICEMI.2009.5274634