Journal article
Application of cyclic coherence function to bearing fault detection in a wind turbine generator under electromagnetic vibration
Mechanical systems and signal processing, Vol.87(PA), pp.279-293
03/15/2017
DOI: 10.1016/j.ymssp.2016.10.026
Abstract
In a wind turbine generator, there is an intrinsic electromagnetic vibration originated from an alternating magnetic field acting on a low stiffness stator, which modulates vibration signals of the generator and impedes fault feature extraction of bearings. When defects arise in a bearing, the statistics of the vibration signal are periodic and this phenomenon is described as cyclostationarity. Correspondingly, cyclostationary analysis enables finding the degree of cyclostationarity representing potential fault modulation information. In this paper, the electromagnetic vibration acting as a disturbance source for fault feature extraction is deduced. Additionally, the spectral correlation density and cyclic coherence function used for vibration analysis are estimated. A real 2MW wind turbine generator with a faulty bearing was tested and the vibration signals were analyzed separately using conventional demodulation analysis, cyclic coherence function, complex wavelet transform and spectral kurtosis. The analysis results have demonstrated that the cyclic coherence function can detect the fault feature of inner race successfully, while the feature is concealed by intensive electromagnetic vibration in the other three methods. The disassembled bearing of the wind turbine generator illustrates the effectiveness of the analysis result, and precautionary measures for protecting bearings in generators are suggested.
•The electromagnetic vibration acting as a disturbance source for fault feature extraction in wind turbine generators is deduced.•Cyclic coherence function is applied to detect bearing fault feature hidden in intensive electromagnetic vibration successfully.•The fault mechanism of shaft current corrosion is illustrated and the precautions are given to prevent this fault in wind turbine generators.
Details
- Title: Subtitle
- Application of cyclic coherence function to bearing fault detection in a wind turbine generator under electromagnetic vibration
- Creators
- Wei Teng - North China Electric Power UniversityXian Ding - North China Electric Power UniversityYangyang Zhang - North China Electric Power UniversityYibing Liu - North China Electric Power UniversityZhiyong Ma - North China Electric Power UniversityAndrew Kusiak - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Mechanical systems and signal processing, Vol.87(PA), pp.279-293
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.ymssp.2016.10.026
- ISSN
- 0888-3270
- eISSN
- 1096-1216
- Grant note
- DOI: 10.13039/501100001809, name: National Natural Science Foundation of China, award: 51305135; DOI: 10.13039/501100012226, name: Fundamental Research Funds for the Central Universities of China, award: 2015ZD15; name: Science and Technology Plan Projects of Hebei, award: 15214307D; name: National High Technology Research and Development Program of China, award: 2015AA043702
- Language
- English
- Date published
- 03/15/2017
- Academic Unit
- Nursing; Industrial and Systems Engineering
- Record Identifier
- 9984186966802771
Metrics
2 Record Views