Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis

查看全文 作　　者：HE [1,2]WangPeng;ZI [1,2]YanYang;CHEN [1,2]BinQiang;WANG [1,2]Shuai;HE [1,2]ZhengJia

机构地区：[1]School of Mechanical Engineering,Xi'an Jiaotong University;[2]State Key Laboratory for Manufacturing Systems Engineering,Xi'an Jiaotong University

出　　处：《Science China(Technological Sciences)》索引2013年第56卷第8期,共10页

基　　金：supported by the National Natural Science Foundation of China (Grant No. 51275384);the Key Project of National Natural Science Foundation of China (Grant No. 51035007);the Important National Science and Technology Specific Projects (Grant No. 2010ZX04014-016);the National Basic Research Program of China ('973' Program) (Grant No. 2009CB724405) 摘　　要：Fault diagnosis of rotating machinery is of great importance to the high quality products and long-term safe operation.However,the useful weak features are usually corrupted by strong background noise,thus increasing the difficulty of the feature extraction.Thereby,a novel denoising method based on the tunable Q-factor wavelet transform(TQWT)using neighboring coefficients is proposed in this article.The emerging TQWT possesses excellent properties compared with the conventional constant-Q wavelet transforms,which can tune Q-factor according to the oscillatory behavior of the signal.Meanwhile,neighboring coefficients denoising is adopted to avoid the overkill of conventional term-by-term thresholding techniques.Because of having the combined advantages of the two methods,the presented denoising method is more practical and effective than other methods.The proposed method is applied to a simulated signal,a rolling element bearing with an outer race defect from antenna transmission chain and a gearbox fault detection case.The processing results demonstrate that the proposed method can successfully identify the fault features,showing that this method is more effective than the conventional wavelet thresholding denoising methods,term-by-term TQWT denoising schemes and spectral kurtosis. 关键词：机械故障诊断去噪方法小波变换 Q因子可调谐应用旋转邻国

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Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis

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