Research on bearing diagnosis technology based on wavelet transform and one-dimensional convolutional neural network
Research on bearing diagnosis technology based on wavelet transform and one-dimensional convolutional neural network
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Outdoor Sling Swivel Chair (set of 2) Aiming at the fault diagnosis of rolling element bearings, propose a method for fine diagnosis of bearings based on wavelet transform and one-dimensional convolutional neural network.First use wavelet transform to decompose the experimental data; Use the resulting low-frequency signal as a one-dimensional convolutional neural network input, bearing fault identification.The experiment SPST 12volt Relay uses the deep groove ball bearing of Case Western Reserve University as the research object, Use this method to identify the normal and outer ring faults of the bearing.the result shows: This method can be effectively applied to the precise identification of bearings.
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