Title :
The fault vibration signal analysis of wind turbine gearbox based on wavelet transform
Author :
Zhang Yan ; Liu Xiang-jun
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
In wind turbine gearbox fault diagnosis, the signals from sensors are non-stationary vibration signals; on the impact of the wind turbine work environment, the vibration signal contains a lot of noise; The traditional signal processing methods cannot extract the fault characteristics fast and effectively from the vibration signals; this paper uses wavelet threshold value denoising method to analyze the wind turbine vibration signals and proves feasibility and practicability of the method through a example.
Keywords :
fault diagnosis; gears; mechanical engineering computing; signal denoising; vibrations; wavelet transforms; wind turbines; fault characteristics; fault vibration signal analysis; nonstationary vibration signals; sensor signals; wavelet threshold value denoising method; wavelet transform; wind turbine gearbox fault diagnosis; wind turbine vibration signals; wind turbine work environment; Frequency modulation; Vibrations; fault diagnosis; wavelet denoising; wind turbines;
Conference_Titel :
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-1390-9
DOI :
10.1109/MIC.2013.6758063