Fault diagnosis of rolling element bearing based on ensemble empirical mode decomposition and cross energy operator

被引:0
|
作者
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing [1 ]
100083, China
机构
来源
关键词
D O I
10.13374/j.issn2095-9389.2015.s1.011
中图分类号
学科分类号
摘要
15
引用
收藏
相关论文
共 50 条
  • [41] Fault Diagnosis of Rolling Bearing Based on an Improved Denoising Technique Using Complete Ensemble Empirical Mode Decomposition and Adaptive Thresholding Method
    Prashant Kumar Sahu
    Rajiv Nandan Rai
    Journal of Vibration Engineering & Technologies, 2023, 11 : 513 - 535
  • [42] Rolling bearing fault diagnosis based on improved complete ensemble empirical mode of decomposition with adaptive noise combined with minimum entropy deconvolution
    Rabah, Abdelkader
    Abdelhafid, Kaddour
    JOURNAL OF VIBROENGINEERING, 2018, 20 (01) : 240 - 257
  • [43] Rolling Bearing Fault Diagnosis Based on an Improved Denoising Method Using the Complete Ensemble Empirical Mode Decomposition and the Optimized Thresholding Operation
    Abdelkader, Rabah
    Kaddour, Abdelhafid
    Bendiabdellah, Azeddine
    Derouiche, Ziane
    IEEE SENSORS JOURNAL, 2018, 18 (17) : 7166 - 7172
  • [44] Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator
    Zhang D.
    Feng Z.-P.
    Feng, Zhi-Peng (fengzp@ustb.edu.cn), 1600, Science Press (38): : 1327 - 1334
  • [45] Fault Diagnosis of Rolling Bearing Based on Adaptive Variational Mode Decomposition and Second‑Order Frequency-Weighted Energy Operator
    Wang X.
    Wen J.
    Ni Z.
    Wu R.
    Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2023, 43 (02): : 246 - 253and406
  • [46] Mode Selection in Variational Mode Decomposition and Its Application in Fault Diagnosis of Rolling Element Bearing
    Yadav, Pradip
    Chauhan, Shivani
    Tiwari, Prashant
    Upadhyay, S. H.
    Rakesh, Pawan Kumar
    RELIABILITY, SAFETY AND HAZARD ASSESSMENT FOR RISK-BASED TECHNOLOGIES, 2020, : 663 - 670
  • [47] The Application of Frequency Family Separation Method in Rolling Bearing Fault diagnosis Based on Empirical Mode Decomposition
    Zhang Bo-Wen
    Qi Wei
    Yang Dong
    Tang Xiaocheng
    Song Zhihuan
    PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE, 2010, : 4033 - 4036
  • [48] Pattern recognition of rolling bearing fault under multiple conditions based on ensemble empirical mode decomposition and singular value decomposition
    Tong, Shuiguang
    Zhang, Yidong
    Xu, Jian
    Cong, Feiyun
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2018, 232 (12) : 2280 - 2296
  • [49] Fault diagnosis of wind turbine bearing based on variational mode decomposition and Teager energy operator
    Zhao, Hongshan
    Li, Lang
    IET RENEWABLE POWER GENERATION, 2017, 11 (04) : 453 - 460
  • [50] Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition
    Georgoulas, George
    Loutas, Theodore
    Stylios, Chrysostomos D.
    Kostopoulos, Vassilis
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 41 (1-2) : 510 - 525