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《Journal of Chinese Society of Power Engineering》 2011-03
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Noise Reduction for Fan Vibration Signals Based on Gaussian Moment Fast ICA Algorithm

ZHOU Yun-long,WANG Suo-bin(School of Energy and Power Engineering,Northeast Dianli University,Jilin 132012,China)  
Experimental tests were carried out to study vibration problems of fans under five different fault conditions,such as the unbalanced rotor,misaligned coupling,loosened fan base,radial friction in rotor and worn inner ring of bearing.By analyzing the ICA theory,a Fast ICA algorithm based on Gaussian moment was proposed and applied for noise reduction of both simulated and actually measured vibration signals of centrifugal fans,after which the results were quantitatively compared with that of EMD and db8 wavelet method.Results show that just as EMD and db8 wavelet method,the Fast ICA algorithm can also effectively deal with transient signals and the signals mixed with broadband noise,which it is not subject to the de-noising threshold and doesn't need to choose the wavelet function,therefore is more versatile and stable in fan vibration signal pre-processing.
【Fund】: 吉林省教育厅资助项目(2007047)
【CateGory Index】: TB533
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