Rolling Bearing Fault Diagnosis Using Time-Frequency Analysis and Deep Transfer Convolutional Neural Network

Rolling Bearing Fault Diagnosis Using Time-Frequency Analysis and Deep Transfer Convolutional Neural Network

Due to the advantage of automatically extracting features from raw data, deep learning (DL) has been increasingly favored in the field of machine fault diagnosis. However, DL exposes the problems of large sample size and long training time, and in actual working conditions, the amount of labeled fau...

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Bibliographic Details
Main Authors: Zhihao Chen, Jian Cen, Jianbin Xiong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Fault diagnosis
rolling bearing
convolutional neural network
continuous wavelet transform
transfer learning
Online Access:https://ieeexplore.ieee.org/document/9167237/

Internet

https://ieeexplore.ieee.org/document/9167237/

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