Highly Imbalanced Fault Diagnosis of Rolling Bearings Based on Variational Mode Gaussian Distortion and Deep Residual Shrinkage Networks

被引:0
|
作者
Zhang, Zhijin [1 ]
Zhang, Chunlei [1 ]
Li, He [1 ]
机构
[1] Northeastern University, School of Mechanical Engineering and Automation, Shenyang,110819, China
关键词
Data augmentation - Deep residual shrinkage network - Faults diagnosis - Features extraction - Imbalanced fault diagnose - Rolling bearings - Vibration;
D O I
10.1109/TIM.2023.3308256
中图分类号
学科分类号
摘要
30
引用
收藏
相关论文
共 50 条
  • [31] Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition and Genetic Algorithm-Optimized Wavelet Threshold Denoising
    Hu, Can
    Xing, Futang
    Pan, Shuhan
    Yuan, Rui
    Lv, Yong
    [J]. MACHINES, 2022, 10 (08)
  • [32] Weak Fault Diagnosis Method of Rolling Bearings Based on Variational Mode Decomposition and a Double-Coupled Duffing Oscillator
    Shan, Shijie
    Zheng, Jianming
    Wang, Kai
    Chen, Ting
    Shi, Yuhua
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (14):
  • [33] Intelligent fault diagnosis of rolling bearings under imbalanced data conditions using attention-based deep learning method
    Li, Jun
    Liu, Yongbao
    Li, Qijie
    [J]. MEASUREMENT, 2022, 189
  • [34] Fault Diagnosis of Rolling Element Bearings Based on Ensemble Empirical Mode Decomposition
    Feng Zhipeng
    Chen Yanjuan
    Ma Fei
    Liu Li
    Hao Rujiang
    Chu Fulei
    [J]. 2011 30TH CHINESE CONTROL CONFERENCE (CCC), 2011, : 2992 - 2995
  • [35] Fault diagnosis for rolling bearings based on generalised dispersive mode decomposition and accugram
    Zhong, Xianyou
    He, Liu
    Wan, Gang
    Zhao, Yang
    [J]. INSIGHT, 2024, 66 (02) : 74 - 81
  • [36] Power spectral density-guided variational mode decomposition for the compound fault diagnosis of rolling bearings
    Yi, Cai
    Wang, Hao
    Ran, Le
    Zhou, Lu
    Lin, Jianhui
    [J]. MEASUREMENT, 2022, 199
  • [37] A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis
    Ni, Qing
    Ji, J. C.
    Feng, Ke
    Halkon, Benjamin
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 164
  • [38] Study on planetary gear fault diagnosis based on variational mode decomposition and deep neural networks
    Li, Yong
    Cheng, Gang
    Liu, Chang
    Chen, Xihui
    [J]. MEASUREMENT, 2018, 130 : 94 - 104
  • [39] Fault Diagnosis for Rolling Bearing Based on Deep Residual Neural Network
    Sun, Yi
    Gao, Hongli
    Hong, Xin
    Song, Hongliang
    Liu, Qi
    [J]. 2018 INTERNATIONAL CONFERENCE ON SENSING, DIAGNOSTICS, PROGNOSTICS, AND CONTROL (SDPC), 2018, : 421 - 425
  • [40] Deep Residual Shrinkage Networks with Self-Adaptive Slope Thresholding for Fault Diagnosis
    Zhang, Zhijin
    Li, He
    Chen, Lei
    [J]. PROCEEDINGS OF 2021 7TH INTERNATIONAL CONFERENCE ON CONDITION MONITORING OF MACHINERY IN NON-STATIONARY OPERATIONS (CMMNO), 2021, : 236 - 239