您当前的位置：
首页 >
文章列表页 >
Rolling bearing fault diagnosis based on variational mode extraction and lightweight network
更新时间：2025-08-04

    • Rolling bearing fault diagnosis based on variational mode extraction and lightweight network

    • “In the field of rolling bearing fault diagnosis, experts have designed a method that combines variational mode extraction with lightweight CNN, effectively improving the fault recognition rate and diagnostic stability in complex environments.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 6, Pages: 1883-1891(2025)
    • 作者机构：

      沈阳航空航天大学 自动化学院，沈阳 110136

    • DOI：10.13229/j.cnki.jdxbgxb.20231047    

      CLC： TH17;TP277

    • Received：04 October 2023，

      Published：01 June 2025

    移动端阅览

  • FENG Zhi-gang,WANG Shou-qi,YU Ming-yue.Rolling bearing fault diagnosis based on variational mode extraction and lightweight network[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(06):1883-1891. DOI： 10.13229/j.cnki.jdxbgxb.20231047.

  •  
  •  

0

Views

8

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Bearing fault diagnosis based on attention for multi-scale convolutional neural network
Bearing fault diagnosis method under unbalanced data distribution
Stable anti⁃noise fault diagnosis of rolling bearing based on CNN⁃BiLSTM
Rolling bearing fault diagnosis method via wavelet packet logarithmic-energy map
Rolling bearing fault diagnosis based on optimized A-BiLSTM

Related Author

SHANG Ji-yang
YU Guang-jie
HAO Jun
ZHANG Xi-jun
HE Zhi-Dong
WANG Jin-hua
CAO Jie
YU Ping

Related Institution

School of Computer and Communication， Lanzhou University of Technology
College of Electrical & Information Engineering， Lanzhou University of Technology
Engineering Research Center of Urban Railway Transportation of Gansu Province
Engineering Research Center of Manufacturing Information of Gansu Province
National Experimental Teaching Center of Electrical and Control Engineering， Lanzhou University of Technology
0