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《Renewable Energy Resources》 2017-03
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Fault feature extraction for bearings of wind turbine based on WATD bispectrum analysis

Cheng Jing;Wang Weiqing;He Shan;Zhang Xinyan;College of Electric Engineering,Xinjiang University,Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Technology;  
Fault diagnosis for bearings is the key to ensure the reliable operation of wind turbine as the large rotating machinery,and the fault feature extraction is the core of fault diagnosis technology.According to the characteristics of wind turbine bearing dynamic signal with strong interference, nonstationary,non Gauss and non-linear,and has trouble in extracting fault characteristics,a feature extraction method based on WATD and bispectrum analysis for wind turbine bearings is proposed. By the Matlab software platform,this method is analyzed,tested and simulated to verify its feasibility. The comparative analysis results show that this method is more rapid and effective,and provide a theoretical basis for the fault diagnosis of wind turbine in practical engineering.
【Fund】: 国家自然科学基金项目(51667020;51367015)
【CateGory Index】: TM315;TH133.3
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【Co-citations】
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1 Cheng Jing;Wang Weiqing;He Shan;Zhang Xinyan;College of Electric Engineering,Xinjiang University,Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Technology;;Fault feature extraction for bearings of wind turbine based on WATD bispectrum analysis[J];可再生能源;2017-03
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