Application research of lifting wavelet transform in fault diagnosis of coal mine bearing

In view of fault diagnosis problem of antifriction bearing in mine critical equipment, the paper proposed to apply lifting wavelet transform to fault diagnosis of coal mine bearing, introduced principle of lifting wavelet transform, and designed adaptive lifting wavelet predictor and upgraded filter. The simulation results show that average error of actual measurement value and theoretical value of bearing fault signal is less than 3%, which indicates that the use of lifting wavelet transform enables accurate identification of bearing fault signal under noisy conditions.