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An enhanced cyclostationary method and its application on the incipient fault diagnosis of induction motors.

Authors :
Wang, Zuolu
Li, Haiyang
Feng, Guojin
Zhen, Dong
Gu, Fengshou
David Ball, Andrew
Source :
Measurement (02632241). Nov2023, Vol. 221, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• The proposed method extends the cyclic frequency range to Fs /2. • The designed scale factor in CWT can help locate important frequency bands. • TKEO is improved to process the single-carrier signal in the frequency domain. • The developed method can enhance the fault features effectively. • Induction motor tests validate the superiority of the method for early fault detection. The cyclostationary analysis techniques have been extensively explored for the purpose of fault detection in rotating machinery. However, there are still huge challenges because of both limited detection frequency range and low fault identification accuracy. This paper proposes an improved cyclostationary method to enhance incipient fault features. Firstly, the continuous wavelet transform is used to accurately locate important frequency bands, and the fault modulation mechanism or fast kurtogram can be adopted to design the optimal wavelet transform scale factor. Secondly, the Teager-Kaiser energy operator is improved to be used in the frequency domain for the weak fault feature enhancement. Finally, fault features are presented in the cyclic frequency domain through spectral coherence and enhanced envelope spectrum. The proposed method is verified through both numerical simulation and experiments, including incipient half-broken rotor bar, and rolling bearing outer race faults in induction motors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02632241
Volume :
221
Database :
Academic Search Index
Journal :
Measurement (02632241)
Publication Type :
Academic Journal
Accession number :
173314741
Full Text :
https://doi.org/10.1016/j.measurement.2023.113475