Time-Frequency Analysis Based on Improved Variational Mode Decomposition and Teager Energy Operator for Rotor System Fault Diagnosis

A time-frequency analysis method based on improved variational mode decomposition and Teager energy operator (IVMD-TEO) is proposed for fault diagnosis of turbine rotor. Variational mode decomposition (VMD) can decompose a multicomponent signal into a number of band-limited monocomponent signals and...

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Bibliographic Details
Published in:Mathematical Problems in Engineering 2016-01, Vol.2016 (2016), p.1045-1053
Main Authors: He, Yu-Ling, Wang, Xiaolong, Tang, Gui-Ji, Liu, Shangkun
Format: Article
Language:English
Subjects:
Algorithms
Correlation coefficients
Decomposition
Demodulation
Fault diagnosis
Kalman filters
Mathematical problems
Operators (mathematics)
Random variables
Representations
Rotors
Spectrum allocation
Time-frequency analysis
Turbines
Wavelet transforms
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Summary:A time-frequency analysis method based on improved variational mode decomposition and Teager energy operator (IVMD-TEO) is proposed for fault diagnosis of turbine rotor. Variational mode decomposition (VMD) can decompose a multicomponent signal into a number of band-limited monocomponent signals and can effectively avoid model mixing. To determine the number of monocomponents adaptively, VMD is improved using the correlation coefficient criterion. Firstly, IVMD algorithm is used to decompose a multicomponent signal into a number of monocompositions adaptively. Second, all the monocomponent signals’ instantaneous amplitude and instantaneous frequency are demodulated via TEO, respectively, because TEO has fast and high precision demodulation advantages to monocomponent signal. Finally, the time-frequency representation of original signal is exhibited by superposing the time-frequency representations of all the monocomponents. The analysis results of simulation signal and experimental turbine rotor in rising speed condition demonstrate that the proposed method has perfect multicomponent signal decomposition capacity and good time-frequency expression. It is a promising time-frequency analysis method for rotor fault diagnosis.
ISSN:1024-123X
1563-5147
DOI:10.1155/2016/1713046