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

Blog Article

Aiming at the fault diagnosis of rolling element bearings, propose virginia mill works tobacco road acacia 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 uses the deep groove ball bearing of Case Western Reserve University as the research object, Use this method to identify the normal and g5210t-p90 outer ring faults of the bearing.the result shows: This method can be effectively applied to the precise identification of bearings.