Review of Bearing Fault Diagnosis Based on Convolutional Neural Network
The diagnosis of bearing faults has always been a major challenge in the field of diagnosis. Early detection of bearing faults can help reduce losses and prevent potential hazards. This paper aims to systematically review the application of convolutional neural network in the field of bearing fault diagnosis. This paper analyzes the structure and principle of convolutional neural network model in detail,expounds its development process in the field of bearing fault diagnosis,and deeply discusses the characteristics of common public data sets. In addition,the article reviews the advantages and disadvantages of convolutional neural networks in bearing fault diagnosis,and discusses the current difficulties and possible future research directions.
NETL
NSTL
万方数据
