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- W2373728944 abstract "Local mean decomposition(LMD) method is a new adaptive time-frequency analysis method,it is successfully applied in rolling bearing fault diagnosis.However,LMD method is sensitive to noise.In order to eliminate influence of noise on result of diagnosis,a fault diagnosis approach for rolling bearing based on wavelet packet de-noising and local mean decomposition(LMD) was proposed.Firstly,wavelet packet was used to remove noise from a signal.Then,the de-noised signal was decomposed with LMD,and the correlation coefficient between the PF components after decomposition and the signal befor decomposition was used as the standard of judgment,the redundant low-frequency PF components were eliminated.Finally,the effective PF set was selected to conduct the power spectral analysis and the fault features were extracted.The comparison between the simulation data and the actual rolling bearing fault diagnosis tests data showed that the proposed method is effective." @default.
- W2373728944 created "2016-06-24" @default.
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- W2373728944 date "2012-01-01" @default.
- W2373728944 modified "2023-09-23" @default.
- W2373728944 title "Fault diagnosis of a rolling bearing using Wavelet packet de-noising and LMD" @default.
- W2373728944 hasPublicationYear "2012" @default.
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