Bearing fault diagnosis of direct-drive wind turbines using multiscale filtering spectrum

2016 ◽  
Author(s):  
Jun Wang ◽  
Yayu Peng ◽  
Wei Qiao
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbines ◽  
Direct Drive ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Multiscale Filtering

scholarly journals Bearing Fault Diagnosis for Direct-Drive Wind Turbines via Current-Demodulated Signals

2013 ◽  
Vol 60 (8) ◽  
pp. 3419-3428 ◽  
Author(s):  
Xiang Gong ◽  
Wei Qiao
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Economic Benefits ◽  
Direct Drive ◽  
Current Frequency ◽  
Bearing Faults ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Stator Current

Bearing faults account for a large portion of all faults in wind turbine generators (WTGs). Current-based bearing fault diagnosis techniques have great economic benefits and are potential to be adopted by the wind energy industry. This paper models the modulation effects of bearing faults on the stator currents of a direct-drive wind turbine equipped with a permanent-magnet synchronous generator (PMSG) operating with a variable shaft rotating frequency. Based on the analysis, a method consisting of appropriate current frequency and amplitude demodulation algorithms and a 1P-invariant power spectrum density algorithm is proposed for bearing fault diagnosis of variable-speed direct-drive wind turbines using only one-phase stator current measurements, where 1P frequency stands for the shaft rotating frequency of a wind turbine. Experimental results on a direct-drive wind turbine equipped with a PMSG operating in a wind tunnel are provided to verify the proposed fault diagnosis method. The proposed method is demonstrated to have advantages over the method of directly using stator current measurements for WTG bearing fault diagnosis.

Rolling Bearing Fault Diagnosis Based on Wavelet Packet and Improved BP Neural Network for Wind Turbines

2013 ◽  
Vol 347-350 ◽  
pp. 117-120
Author(s):  
Zhao Ran Hou
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Frequency Domain ◽  
Wind Turbines ◽  
Wavelet Packet ◽  
Roller Bearing ◽  
Rolling Bearing ◽  
Transmission System ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis

Vibration signal was a carrier of fault features of the wind turbine transmission system, it can reflect most of the fault information of the wind turbine transmission system. According to the frequency domain features of the roller bearing fault, wavelet packet transform for feature extraction was proposed as the characteristics of wind turbines in the presence of a large number of transient and non-stationary signals. The characteristics of wavelet packet was analyzed, combined with the wind turbines in the rolling bearing fault characteristic vibration extraction methods, the rolling bearing fault diagnosis was realized through the wavelet packet decomposition and reconstruction, the procedure was given. The simulation result shows that this application can reflect relationship of the failure characteristics and frequency domain feature vectors, also the nonlinear mapping ability of neural networks was played and the fault diagnosis capability enhanced.

scholarly journals A review of bearing fault diagnosis for wind turbines

2021 ◽  
Vol 675 (1) ◽  
pp. 012094
Author(s):  
Bing Liu ◽  
Baixin Liu ◽  
Qingbin Dai ◽  
Huaping Liu
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbines ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis
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