Bearing degradation trend prediction under different operational conditions based on CNN-LSTM

摘要

Bearing degradation research is an important part in condition-based maintenance.This paper tries to propose an end-to-end model to realize bearing degradation trend prediction by vibration signals.Convolution neural network is good at data dimension reduction and feature extraction,and long short-term memory is good at deal with time sequences.The experiment proves that the combination of the two deep learning methods has a good effect,which avoid some disadvantages of traditional methods.Results shows that the model has application value in industrial practice.