Research on bearing diagnosis technology based on wavelet transform and one-dimensional convolutional neural network

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