Bearing intelligent fault diagnosis
Bearing vibration signal is a kind of time series data, and its time dimension characteristic plays a key role in classification. Using convolutional neural network (CNN) alone to diagnose bearing fault will cause the loss of time dimension information. This results in the decline of diagnosis accur...
Main Authors: | WU Dongmei, WANG Fuqi, LI Xiangong, TANG Run, ZHANG Xinjian |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Department of Industry and Mine Automation
2022-09-01
|
Series: | Gong-kuang zidonghua |
Subjects: | |
Online Access: | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.17986 |
Similar Items
-
A Bearing Fault Diagnosis Method Based on Dilated Convolution and Multi-Head Self-Attention Mechanism
by: Peng Hou, et al.
Published: (2023-11-01) -
Bearing Fault Diagnosis Based on Multi-Scale CNN and Bidirectional GRU
by: Taher Saghi, et al.
Published: (2022-12-01) -
Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model
by: Kaixu Han, et al.
Published: (2024-12-01) -
A fault diagnosis method for flexible converter valve equipment based on DSC-BIGRU-MA
by: Jianbao Guo, et al.
Published: (2024-04-01) -
Fault diagnosis of rolling bearing based on deep convolutional neural network and gated recurrent unit
by: Zhexin ZHOU, et al.
Published: (2023-01-01)