Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext

Chao Zhang, Feifan Qin, Wentao Zhao, Jianjun Li, Tongtong Liu

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DOI: 10.3390/s23115334
Published: 2023-06-05
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s23115334,
  title = {Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext},
  author = {Chao Zhang and Feifan Qin and Wentao Zhao and Jianjun Li and Tongtong Liu},
  year = {2023},
  journal = {Sensors},
  doi = {10.3390/s23115334},
  url = {https://doi.org/10.3390/s23115334}
}

RIS

TY  - JOUR
TI  - Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext
AU  - Chao Zhang
AU  - Feifan Qin
AU  - Wentao Zhao
AU  - Jianjun Li
AU  - Tongtong Liu
PY  - 2023
JO  - Sensors
DO  - 10.3390/s23115334
UR  - https://doi.org/10.3390/s23115334
ER  -

APA

Zhang, C., Qin, F., Zhao, W., Li, J., & Liu, T. (2023). Research on Rolling Bearing Fault Diagnosis Based on Digital Twin Data and Improved ConvNext. Sensors. https://doi.org/10.3390/s23115334

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crossref · retrieved 2026-09-26T07:33:19.014Z