Research on Bearing Fault Diagnosis Method Based on Filter Features of MOMLMEDA and LSTM
As the supporting unit of rotating machinery, bearing can ensure efficient operation of the equipment.Therefore, it is very important to monitor the status of bearings accurately.A bearing fault diagnosis mothed based on Multipoint Optimal Minimum Local Mean Entropy Deconvolution Adjusted (MOMLMEDA) and Long Short-Term Memory (LSTM) is proposed.MOM