Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis

被引：0
|
作者：
Cai, Yuxiang [1 ]
Wang, Zhenya [1 ]
Yao, Ligang [1 ]
Lin, Tangxin [1 ]
Zhang, Jun [1 ]
机构：
[1] School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou,350108, China
来源：
Computational Intelligence and Neuroscience | 2022年 / 2022卷
关键词：
461.4 Ergonomics and Human Factors Engineering - 601.1 Mechanical Devices - 716.1 Information Theory and Signal Processing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
44
引用
收藏
相关论文
共 50 条
  • [1] Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis
    Cai, Yuxiang
    Wang, Zhenya
    Yao, Ligang
    Lin, Tangxin
    Zhang, Jun
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [2] Application of adaptive convolutional neural network in rotating machinery fault diagnosis
    Li T.
    Duan L.
    Zhang D.
    Zhao S.
    Huang H.
    Bi C.
    Yuan Z.
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2020, 39 (16): : 275 - 282and288
  • [3] Fault Diagnosis of Rotating Machinery Based on Evolutionary Convolutional Neural Network
    Bai, Yihao
    Cheng, Weidong
    Wen, Weigang
    Liu, Yang
    [J]. SHOCK AND VIBRATION, 2022, 2022
  • [4] Ensemble adaptive convolutional neural networks with parameter transfer for rotating machinery fault diagnosis
    Zhao, Ke
    Jiang, Hongkai
    Li, Xingqiu
    Wang, Ruixin
    [J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2021, 12 (05) : 1483 - 1499
  • [5] Ensemble adaptive convolutional neural networks with parameter transfer for rotating machinery fault diagnosis
    Ke Zhao
    Hongkai Jiang
    Xingqiu Li
    Ruixin Wang
    [J]. International Journal of Machine Learning and Cybernetics, 2021, 12 : 1483 - 1499
  • [6] Image representation of vibration signals and its application on fault diagnosis of rotating machinery with convolutional neural network: A benchmark study
    [J]. Zhang, Jianqun (zhang_jianqun@tongji.edu.cn), 2025, 239 (02) : 532 - 564
  • [7] Rotating machinery fault diagnosis based on a novel lightweight convolutional neural network
    Yan, Jing
    Liu, Tingliang
    Ye, Xinyu
    Jing, Qianzhen
    Dai, Yuannan
    [J]. PLOS ONE, 2021, 16 (08):
  • [8] A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network
    Guo, Sheng
    Yang, Tao
    Gao, Wei
    Zhang, Chen
    [J]. SENSORS, 2018, 18 (05)
  • [9] A Cooperative Convolutional Neural Network Framework for Multisensor Fault Diagnosis of Rotating Machinery
    Yu, Tianzhuang
    Jiang, Zeyu
    Ren, Zhaohui
    Zhang, Yongchao
    Zhou, Shihua
    Zhou, Xin
    [J]. IEEE Sensors Journal, 2024, 24 (22): : 38309 - 38317
  • [10] A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery
    Ma, Shangjun
    Cai, Wei
    Liu, Wenkai
    Shang, Zhaowei
    Liu, Geng
    [J]. SENSORS, 2019, 19 (10)
12345