Abstract
Because AE (Acoustic Emission) signals in bearing fault monitoring unavoidably mixed various noise which lead to wide band characteristics, in this paper, the collected AE signals are pre-processed by EMD (Empirical Mode Decomposition) algorithm to extract useful information in the concerned frequency range, after that, power spectrum is used to locating analysis and pattern recognition. Experiment show that this method could improve the detection accuracy in rolling element bearing fault diagnosis.
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