Improved Generative Adversarial Network for Rotating Component Fault Diagnosis in Scenarios With Extremely Limited Data

Jianguo Miao, Jianyu Wang, Dingcheng Zhang, Qiang Miao. Improved Generative Adversarial Network for Rotating Component Fault Diagnosis in Scenarios With Extremely Limited Data. IEEE T. Instrumentation and Measurement, 71:1-13, 2022. [doi]

@article{MiaoWZM22,
  title = {Improved Generative Adversarial Network for Rotating Component Fault Diagnosis in Scenarios With Extremely Limited Data},
  author = {Jianguo Miao and Jianyu Wang and Dingcheng Zhang and Qiang Miao},
  year = {2022},
  doi = {10.1109/TIM.2021.3127636},
  url = {https://doi.org/10.1109/TIM.2021.3127636},
  researchr = {https://researchr.org/publication/MiaoWZM22},
  cites = {0},
  citedby = {0},
  journal = {IEEE T. Instrumentation and Measurement},
  volume = {71},
  pages = {1-13},
}