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Digital signal processing algorithms are widely adopted in motor bearing fault diagnosis. However, most algorithms are developed on desktop platforms, and their focus is on the analysis of offline captured signals. In this paper, a simple and easily implemented algorithm running on an embedded system is proposed for the online fault diagnosis of motor bearing. The core part of the algorithm is a stochastic-resonance-based...
In this paper, we attempted to classify the acceleration signals of different working states of bearings by using the wavelet-based fractal analysis. Considering the similarity of the power spectrums between bearing vibration signals and 1/f processes signals, the principles of wavelet-based fractal analysis for bearing fault diagnosis are explored. To verify the feasibility and practicability of...
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