Fault Diagnosis Method of Wind Turbine Bearing based on Variational Mode Decomposition and Spectrum Kurtosis

DOI

10.2991/mmme-16.2016.168How to use a DOI?

Keywords

Wind Turbine; Fault Diagnosis; Variational Mode Decomposition; Spectrum Kurtosis; Bearing

Abstract

Aiming at the problem that fault feature of wind turbine bearing is difficult to extract, a new fault diagnosis method based on variational modal decomposition (VMD) and spectral kurtosis (SK) is proposed in this pa-per. Firstly, vibration signal collected from wind turbine is decomposed into several intrinsic mode functions (IMFs) by VMD. Secondly, Fourier transform is applied to each IMF and the absolute values of spectral sig-nals are calculated. Thirdly, using the filter characteristics of spectral kurtosis (SK), the resonance frequency band caused by defects is selected to construct the optimal envelope. Finally, the defect of wind turbine bear-ing can be diagnosed by analyzing the envelope spectrum. The experimental results show that the VMD-SK method can successfully extract the fault characteristic frequency and effectively distinguish the bearing fault of wind turbine.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ying Zhang
AU  - Yichi Zhang
AU  - Chao Zhang
AU  - Hua Yu
AU  - Lu Bai
AU  - Jie Hao
AU  - Yu Han
PY  - 2016/10
DA  - 2016/10
TI  - Fault Diagnosis Method of Wind Turbine Bearing based on Variational Mode Decomposition and Spectrum Kurtosis
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 705
EP  - 708
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.168
DO  - 10.2991/mmme-16.2016.168
ID  - Zhang2016/10
ER  -