Bearing Fault Diagnosis based on Feature Visualization and Depth Adaptive Network
Aiming at the problem that feature extraction in bearing fault diagnosis needs to rely heavily on manual experience and expert knowledge,a bearing fault diagnosis method based on Gramian angle field(GAF) transformation and adaptive depth network is proposed. Firstly,the collected signals are analyze...
Saved in:
| Main Authors: | Hong Jiang, Yu Feng, Rong Fu |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2022-07-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.07.024 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Acoustic fault diagnosis of traction motor bearing based on fusion feature
by: YANG Gang, et al.
Published: (2023-03-01) -
Bearing Fault Diagnosis based on ACSBP Algorithm
by: Cheng Jiatang, et al.
Published: (2017-01-01) -
Rolling Bearing Fault Diagnosis Model Based on Multi-Scale Depthwise Separable Convolutional Neural Network Integrated with Spatial Attention Mechanism
by: Zhixin Jin, et al.
Published: (2025-06-01) -
Locomotive Bearing Fault Diagnosis Using Empirical Wavelet Transform
by: Renjie XU
Published: (2019-09-01) -
Research on Fault Diagnosis of Rolling Bearing based on Synchrosqueezing Extracting Transform
by: Qi Liu, et al.
Published: (2021-01-01)