Rolling bearings fault diagnosis based on two-stage signal fusion and deep multi-scale multi-sensor network

被引：0
|
作者：
Pan, Zuozhou [1 ,2 ]
Guan, Yang [1 ]
Fan, Fengjie [1 ]
Zheng, Yuanjin [2 ]
Lin, Zhiping [2 ]
Meng, Zong [1 ]
机构：
[1] College of Electrical Engineering, Yanshan University, Hebei, Qinhuangdao,066004, China
[2] College of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore
来源：
ISA Transactions | 2024年 / 154卷
关键词：
D O I：
10.1016/j.isatra.2024.08.033
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：311 / 334
相关论文
共 50 条
  • [1] Rolling bearing fault diagnosis method based on multi-sensor two-stage fusion
    Liu, Cang
    Tong, Jinyu
    Zheng, Jinde
    Pan, Haiyang
    Bao, Jiahan
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2022, 33 (12)
  • [2] A rolling bearing fault diagnosis method based on multi-sensor two-stage feature fusion
    Liu, Cang
    Tong, Jinyu
    Bao, Jiahan
    Zheng, Jinde
    Pan, Haiyang
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2022, 41 (08): : 199 - 207
  • [3] Two-Stage Multi-Scale Fault Diagnosis Method for Rolling Bearings with Imbalanced Data
    Zheng, Minglei
    Chang, Qi
    Man, Junfeng
    Liu, Yi
    Shen, Yiping
    [J]. MACHINES, 2022, 10 (05)
  • [4] Fault diagnosis of rolling bearings based on multi-scale deep subdomain adaptation network
    Zhou, Qin
    Su, Zuqiang
    Liu, Lanhui
    Hu, Xiaolin
    Yu, Jianhang
    [J]. Journal of Intelligent and Fuzzy Systems, 2022, 43 (01): : 575 - 585
  • [5] Fault diagnosis of rolling bearings based on multi-scale deep subdomain adaptation network
    Zhou, Qin
    Su, Zuqiang
    Liu, Lanhui
    Hu, Xiaolin
    Yu, Jianhang
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 43 (01) : 575 - 585
  • [6] Fault diagnosis of rolling bearing based on feature fusion of multi-scale deep convolutional network
    Wang, Nini
    Ma, Ping
    Zhang, Hongli
    Wang, Cong
    [J]. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2022, 43 (04): : 351 - 358
  • [7] Research on the application of the multi-sensor data fusion technology in fault diagnosis of rolling bearings
    Chen Xia
    Huang Zhichu
    Li WEixuan
    [J]. ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS, 2007, : 3914 - 3917
  • [8] Intelligent fault diagnosis of multi-sensor rolling bearings based on variational mode extraction and a lightweight deep neural network
    Wang, Shouqi
    Feng, Zhigang
    [J]. INTERNATIONAL JOURNAL OF SIGNAL AND IMAGING SYSTEMS ENGINEERING, 2024, 13 (01)
  • [9] Fault diagnosis for rolling element bearings based on multi-sensor signals and CNN
    Zhu, Danchen
    Zhang, Yongxiang
    Pan, Yangyang
    Zhu, Qunwei
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2020, 39 (04): : 172 - 178
  • [10] FAULT DIAGNOSIS OF ROLLING BEARINGS BASED ON MULTI-SCALE ENTROPY AND ENSEMBLED ARTIFICIAL NEURAL NETWORK
    Chen, Fen
    Liu, Quan
    Wei, Qin
    Ting, Deng
    Ting, Yan
    Su Wenqin
    Peng Bingjie
    Zhao, Lei
    [J]. PROCEEDINGS OF THE ASME 9TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2014, VOL 2, 2014,
12345