Rolling Bearing Fault Feature Extraction Using Local Maximum Synchrosqueezing Transform and Global Fuzzy Entropy

被引：0
|
作者：
Zhu, Keheng [1 ]
Yue, Xiucheng [1 ]
Sun, Dejian [1 ]
Xiao, Shichang [1 ]
Hu, Xiong [1 ]
机构：
[1] School of Logistics Engineering, Shanghai Maritime University, Shanghai, 201306, China
来源：
International Journal of Acoustics and Vibrations | 2022年 / 27卷 / 01期
关键词：
Compendex;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Roller bearings
引用
收藏
页码：37 / 44
相关论文
共 50 条
  • [41] Modified kernel global-local marginal fisher analysis for rolling bearing feature extraction
    Tian, Yu
    Guo, Shunsheng
    Jiang, Li
    Li, Yibing
    Zhang, Xin
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2025, 36 (02)
  • [42] Multiscale fuzzy entropy and its application in rolling bearing fault diagnosis
    Zheng, Jin-De
    Chen, Min-Jun
    Cheng, Jun-Sheng
    Yang, Yu
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2014, 27 (01): : 145 - 151
  • [43] A rolling bearing fault diagnosis approach based on LCD and fuzzy entropy
    Zheng, Jinde
    Cheng, Junsheng
    Yang, Yu
    MECHANISM AND MACHINE THEORY, 2013, 70 : 441 - 453
  • [44] Local Optimum Time-Reassigned Synchrosqueezing Transform for Bearing Fault Diagnosis of Rotating Equipment
    Lv, Site
    Zeng, Shan
    Li, Yu
    Yang, Ke
    Chen, Yulong
    IEEE SENSORS JOURNAL, 2024, 24 (07) : 10528 - 10539
  • [45] Multiscale slope feature extraction for gear and bearing fault diagnosis using wavelet transform
    Vishwash, B.
    Pai, Srinivasa P.
    Sriram, N. S.
    Ahmed, Rounaq
    Kumar, H. S.
    Vijay, G. S.
    INTERNATIONAL CONFERENCE ON ADVANCES IN MANUFACTURING AND MATERIALS ENGINEERING (ICAMME 2014), 2014, 5 : 1650 - 1659
  • [46] Fault feature extraction of rolling bearings based on an improved permutation entropy
    Chen X.-L.
    Zhang B.-Z.
    Feng F.-Z.
    Jiang P.-C.
    Feng, Fu-Zhou (fengfuzhou@tsinghua.org.cn), 2018, Nanjing University of Aeronautics an Astronautics (31): : 902 - 908
  • [47] Feature extraction for rolling bearing incipient fault based on maximum correlated kurtosis deconvolution and 1.5 dimension spectrum
    School of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding
    071003, China
    J Vib Shock, 12 (79-84):
  • [48] Feature extraction of rolling bearing fault signal based on local mean decomposition and Teager energy operator
    Cai, Jianhua
    INDUSTRIAL LUBRICATION AND TRIBOLOGY, 2017, 69 (06) : 872 - 880
  • [49] Early fault feature extraction of rolling bearing based on ICD and tunable Q-factor wavelet transform
    Li, Yongbo
    Liang, Xihui
    Xu, Minqiang
    Huang, Wenhu
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 86 : 204 - 223
  • [50] Adaptive Generalized Demodulation Transform Based Rolling Bearing Time-varying Nonstationary Fault Feature Extraction
    Zhao D.
    Wang T.
    Chu F.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2020, 56 (03): : 80 - 87
12345