A New Time-frequency Domain Feature Extraction Method for Rolling Bearing Fault Diagnosis
For fault diagnosis of rolling bearings,a new feature extraction strategy based on short time Fourier transform( STFT) and bag of wordss( BOW) is proposed. Based on the generate mechanism of bearing fault,the different bearing vibration signals have relevant energy distribution. But in the factory,s...
Saved in:
| Main Authors: | Chen Junjie, Wang Xiaofeng, Liu Fei, Zhou Wenjing |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2016-01-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.07.028 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sound-Based Unsupervised Fault Diagnosis of Industrial Equipment Considering Environmental Noise
by: Jeong-Geun Lee, et al.
Published: (2024-11-01) -
Application of Time Domain Index and Kurtosis analysis Method in the Fault Diagnosis of Rolling Bearing
by: Guo Qingfeng, et al.
Published: (2016-01-01) -
Time–Frequency-Domain Fusion Cross-Attention Fault Diagnosis Method Based on Dynamic Modeling of Bearing Rotor System
by: Shiyu Xing, et al.
Published: (2025-07-01) -
Bearing Fault Diagnosis Based on Time–Frequency Dual Domains and Feature Fusion of ResNet-CACNN-BiGRU-SDPA
by: Jarula Yasenjiang, et al.
Published: (2025-06-01) -
An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning
by: Usman Ali, et al.
Published: (2025-01-01)