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《Journal of Zhejiang University(Engineering Science)》 2018-05
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De-noising for vibration signals of wind power generator using empirical wavelet transform

CHEN Xue-jun;YANG Yong-ming;School of Mechanical and Electrical Engineering,Putian University;State Key Laboratory of Power Transmission Equipment and System Security and New Technology,Chongqing University;  
The empirical wavelet transform theory(EWT)and its adaptive characteristics were analyzed according to the nonlinear characteristics of wind power generator vibration signal and the poor monitoring environment.Then a de-noising method was proposed based on EWT.The proposed method was tested by using the leleccum and bearing fault simulation signal with noises,compared with de-noising method based on db1 wavelet with compulsion,db1 wavelet with soft threshold,and sym5 wavelet.The de-noising effect based on EWT was verified for the actual vibration signals of wind power generator.The other three methods were used to eliminate noises analysis and compared with the same signals.The simulation and experimental results show that the de-noising method based on EWT can achieve the same de-noising effect,or even better than the methods based on db1 wavelet with compulsion,db1 wavelet with soft threshold,and sym5 wavelet.The proposed method does not loss the original vibration signals energy,and it is better than the empirical mode decomposition in the adaptive mode decomposition with strong robustness.
【Fund】: 国家自然科学基金资助项目(51477015);; 福建省高校杰出青年科研人才培育计划资助项目(2015054);; 输配电装备及系统安全与新技术国家重点实验室访问学者资助项目(2007DA10512714406);; 莆田市科技资助项目(2016G2021)
【CateGory Index】: TM315
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