Fault Diagnosis Method of Wind Turbine Bearing based on Variational Mode Decomposition and Spectrum Kurtosis
- 10.2991/mmme-16.2016.168How to use a DOI?
- Wind Turbine; Fault Diagnosis; Variational Mode Decomposition; Spectrum Kurtosis; Bearing
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.
- © 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/).
Cite this article
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 -