Bearing Fault Diagnosis Method Based on Local Mean Decomposition and Wigner Higher Moment Spectrum

被引:0
|
作者
J-h. Cai
Q-y. Chen
机构
[1] Hunan Universityof Arts and Science,Department of Physics and Electronics
来源
Experimental Techniques | 2016年 / 40卷
关键词
Local mean decomposition; Wigner higher moment spectrum; Fault diagnosis; Time-frequency analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Combining local mean decomposition (LMD) and Wigner higher moment spectrum (WHOS), a bearing fault diagnosis method was proposed, called LMD-WHOS method. Firstly, LMD decomposed fault diagnosis signal into a series of production function (PF), and then the “real” components were found out from the decomposed components by calculating correlation coefficient between the component and the original signal. Secondly, the WHOS of the selected components was estimated. These estimated spectrums were added up to obtain the WHOS of original signal. Finally diagnosis conclusion can be drawn from the WHOS and its corresponding marginal spectrum. The algorithms of LMD and WHOS were described, and the major steps of proposed method were provided. Simulated signal and some measured rolling bearing fault signal were analyzed based on the presented method, and the results were compared with that of Wigner-Ville distribution (WVD) method. Results show that the proposed method reserves the advantages of LMD and WHOS, and can effectively inhibit the cross-term effect, which arises in Wigner-Ville spectrum. With the new method, the nature of the bearing fault signal is kept exactly and its dynamic changing characteristics of energy distribution with time and frequency can be clearly exhibited in the WHOS spectrum. LMD-WHOS method provides a new way for the accurate judgment of bearing fault state.
引用
收藏
页码:1437 / 1446
页数:9
相关论文
共 50 条
  • [21] Fault Diagnosis of Gear Wear Based on Local Mean Decomposition
    Li, Hui
    ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEM AND MATERIAL ENGINEERING, 2012, 459 : 298 - 302
  • [22] An intelligent self-adaptive bearing fault diagnosis approach based on improved local mean decomposition
    Goyal, Deepam
    Choudhary, Anurag
    Sandhu, Jasminder Kaur
    Srivastava, Prateek
    Saxena, Kuldeep Kumar
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2022,
  • [23] A fault diagnosis scheme for rolling bearing based on local mean decomposition and improved multiscale fuzzy entropy
    Li, Yongbo
    Xu, Minqiang
    Wang, Rixin
    Huang, Wenhu
    JOURNAL OF SOUND AND VIBRATION, 2016, 360 : 277 - 299
  • [24] Fault Diagnosis of Offshore Platforms Using the Local Mean Decomposition Method
    Lin, Jinshan
    FUTURE MATERIALS ENGINEERING AND INDUSTRY APPLICATION, 2012, 365 : 94 - 97
  • [25] Fault Diagnosis Method of Wind Turbine Bearing based on Variational Mode Decomposition and Spectrum Kurtosis
    Zhang, Ying
    Zhang, Yichi
    Zhang, Chao
    Yu, Hua
    Bai, Lu
    Hao, Jie
    Han, Yu
    Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering (MMME 2016), 2016, 79 : 851 - 854
  • [26] Gear fault diagnosis method based on local mean decomposition and generalized morphological fractal dimensions
    Zheng, Zhi
    Jiang, Wanlu
    Wang, Zhenwei
    Zhu, Yong
    Yang, Kai
    MECHANISM AND MACHINE THEORY, 2015, 91 : 151 - 167
  • [27] A bearing fault diagnosis method based on sparse decomposition theory
    张新鹏
    胡茑庆
    胡雷
    陈凌
    JournalofCentralSouthUniversity, 2016, 23 (08) : 1961 - 1969
  • [28] A bearing fault diagnosis method based on sparse decomposition theory
    Xin-peng Zhang
    Niao-qing Hu
    Lei Hu
    Ling Chen
    Journal of Central South University, 2016, 23 : 1961 - 1969
  • [29] Fault diagnosis of gears based on local mean decomposition combing with kurtosis
    Pan, Qiang
    He, Tian
    Shan, Yingchun
    Liu, Xiandong
    JOURNAL OF VIBROENGINEERING, 2014, 16 (06) : 2639 - 2648
  • [30] A bearing fault diagnosis method based on sparse decomposition theory
    Zhang Xin-peng
    Hu Niao-qing
    Hu Lei
    Chen Ling
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2016, 23 (08) : 1961 - 1969