An interpretable data augmentation scheme for machine fault diagnosis based on a sparsity-constrained generative adversarial network

被引:0
|
作者
Ma, Liang [1 ,2 ,3 ]
Ding, Yu [2 ,4 ]
Wang, Zili [1 ,2 ,3 ]
Wang, Chao [1 ,2 ,3 ]
Ma, Jian [1 ,2 ,3 ]
Lu, Chen [1 ,2 ,3 ]
机构
[1] Institute of Reliability Engineering, Beihang University, Beijing,100191, China
[2] Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing,100191, China
[3] School of Reliability and Systems Engineering, Beihang University, Beijing,100191, China
[4] School of Aeronautic Science and Engineering, Beihang University, Beijing,100191, China
关键词
31;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] An interpretable data augmentation scheme for machine fault diagnosis based on a sparsity-constrained generative adversarial network
    Ma, Liang
    Ding, Yu
    Wang, Zili
    Wang, Chao
    Ma, Jian
    Lu, Chen
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2021, 182
  • [2] Generative adversarial networks for data augmentation in machine fault diagnosis
    Shao, Siyu
    Wang, Pu
    Yan, Ruqiang
    [J]. COMPUTERS IN INDUSTRY, 2019, 106 : 85 - 93
  • [3] Data augmentation in fault diagnosis based on the Wasserstein generative adversarial network with gradient penalty
    Gao, Xin
    Deng, Fang
    Yue, Xianghu
    [J]. NEUROCOMPUTING, 2020, 396 : 487 - 494
  • [4] Machine fault diagnosis with small sample based on variational information constrained generative adversarial network
    Liu, Shaowei
    Jiang, Hongkai
    Wu, Zhenghong
    Liu, Yunpeng
    Zhu, Ke
    [J]. ADVANCED ENGINEERING INFORMATICS, 2022, 54
  • [5] Gradient flow-based meta generative adversarial network for data augmentation in fault diagnosis
    Wang, Rugen
    Chen, Zhuyun
    Li, Weihua
    [J]. APPLIED SOFT COMPUTING, 2023, 142
  • [6] Data Augmentation Using Generative Adversarial Network for Automatic Machine Fault Detection Based on Vibration Signals
    Bui, Van
    Pham, Tung Lam
    Nguyen, Huy
    Jang, Yeong Min
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (05): : 1 - 16
  • [7] SPARSE-GAN: SPARSITY-CONSTRAINED GENERATIVE ADVERSARIAL NETWORK FOR ANOMALY DETECTION IN RETINAL OCT IMAGE
    Zhou, Kang
    Gao, Shenghua
    Cheng, Jun
    Gu, Zaiwang
    Fu, Huazhu
    Tu, Zhi
    Yang, Jianlong
    Zhao, Yitian
    Liu, Jiang
    [J]. 2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020), 2020, : 1227 - 1231
  • [8] Data Augmentation Method for Power Transformer Fault Diagnosis Based on Conditional Wasserstein Generative Adversarial Network
    Liu, Yunpeng
    Xu, Ziqiang
    He, Jiahui
    Wang, Quan
    Gao, Shuguo
    Zhao, Jun
    [J]. Dianwang Jishu/Power System Technology, 2020, 44 (04): : 1505 - 1513
  • [9] Generative Adversarial Network With Dual Multiscale Feature Fusion for Data Augmentation in Fault Diagnosis
    Ren, Zhijun
    Ji, Jinchen
    Zhu, Yongsheng
    Hong, Jun
    Feng, Ke
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [10] Data augmentation strategy for power inverter fault diagnosis based on wasserstein distance and auxiliary classification generative adversarial network
    Sun, Quan
    Peng, Fei
    Yu, Xianghai
    Li, Hongsheng
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 237