A hybrid feature selection scheme for unsupervised learning and its application in bearing fault diagnosis (vol 38, pg 11311, 2011)

被引：0
|
作者：
Yang, Yang [1 ]
Liao, Linxia [2 ]
Meng, Guang [1 ]
Lee, Jay [2 ]
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
[2] Univ Cincinnati, NSF I UCR Ctr Intelligent Maintenance Syst, Cincinnati, OH 45221 USA
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2013年 / 40卷 / 02期
关键词：
D O I：
10.1016/j.eswa.2012.07.039
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
引用
收藏
页码：839 / 839
页数：1
相关论文
共 50 条
  • [41] A feature vector with insensitivity to the position of the outer race defect and its application in rolling bearing fault diagnosis
    Zhang, Jianqun
    Zhang, Qing
    Feng, Wenzong
    Qin, Xianrong
    Sun, Yuantao
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2025, 24 (01): : 327 - 350
  • [42] Feature extraction under bounded noise background and its application in low speed bearing fault diagnosis
    Zhang, Jingling
    Yang, Jianhua
    Litak, Grzegorz
    Hu, Eryi
    JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2019, 33 (07) : 3193 - 3204
  • [43] Feature extraction under bounded noise background and its application in low speed bearing fault diagnosis
    Jingling Zhang
    Jianhua Yang
    Grzegorz Litak
    Eryi Hu
    Journal of Mechanical Science and Technology, 2019, 33 : 3193 - 3204
  • [44] Hybrid feature selection method for SVM classification and its application for fault diagnosis of wear and peeling in journal bearing with a little muddy water using long-term real data
    Tu, Yilin
    Inoue, Tsuyoshi
    Yabui, Shota
    Katayama, Keiichi
    Tomimatsu, Shigeyuki
    JOURNAL OF LOW FREQUENCY NOISE VIBRATION AND ACTIVE CONTROL, 2023, 42 (01) : 231 - 252
  • [45] Signal sparse representation method of adaptive learning dictionary and its application in bearing fault diagnosis
    Zhang C.
    Huang W.-G.
    Ma Y.-Q.
    Que H.-B.
    Jiang X.-X.
    Zhu Z.-K.
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2022, 35 (05): : 1278 - 1288
  • [46] Establishment of a deep learning network based on feature extraction and its application in gearbox fault diagnosis
    Wu, QingE
    Guo, Yinghui
    Chen, Hu
    Qiang, Xiaoliang
    Wang, Wei
    ARTIFICIAL INTELLIGENCE REVIEW, 2019, 52 (01) : 125 - 149
  • [47] Frequency band selection based on the kurtosis of the squared envelope spectrum and its application in bearing fault diagnosis
    Hu, Chongqing
    Peng, Zhongxiao
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2016, 230 (7-8) : 1113 - 1125
  • [48] Establishment of a deep learning network based on feature extraction and its application in gearbox fault diagnosis
    QingE Wu
    Yinghui Guo
    Hu Chen
    Xiaoliang Qiang
    Wei Wang
    Artificial Intelligence Review, 2019, 52 : 125 - 149
  • [49] A hybrid denoising model using deep learning and sparse representation with application in bearing weak fault diagnosis
    Zhou, Xin
    Zhou, Haoxuan
    Wen, Guangrui
    Huang, Xin
    Lei, Zihao
    Zhang, Zhifeng
    Chen, Xuefeng
    MEASUREMENT, 2022, 189
  • [50] Independent vector analysis based on binary grey wolf feature selection and extreme learning machine for bearing fault diagnosis
    Souaidia, Chouaib
    Thelaidjia, Tawfik
    Chenikher, Salah
    JOURNAL OF SUPERCOMPUTING, 2023, 79 (06): : 7014 - 7036
12345