Bearing fault diagnosis based on dual-stream CNN using wavelet time-frequency FFT spectrum

The article proposes a method for bearing fault diagnosis based on the waveform FFT spectrum of the dual-stream CNN. The method first uses FFT and wavelet transform to obtain the one-dimensional FFT spectrum and two-dimensional time-frequency map of bearing vibration, and then inputs them into the 1D-CNN channel and 2D-CNN channel of the model for feature extraction. After the feature information is fused and processed, the fault diagnosis is finally completed in the classification layer. The experimental results show that this model significantly improves the accuracy of bearing fault diagnosis.