An End-to-End Fault Diagnosis Model for Rolling Bearings Based on Multi-Scale Convolution and the Kolmogorov–Arnold Network

Donghua Yu, Zhenyu Wang, Jia Liu, Huan Liu, Changtian Ying

Open source

DOI
10.3390/s26134005
Published
2026-06-24
Container
Sensors
Publisher
MDPI AG
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3390/s26134005,
  title = {An End-to-End Fault Diagnosis Model for Rolling Bearings Based on Multi-Scale Convolution and the Kolmogorov–Arnold Network},
  author = {Donghua Yu and Zhenyu Wang and Jia Liu and Huan Liu and Changtian Ying},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26134005},
  url = {https://doi.org/10.3390/s26134005}
}

RIS

TY  - JOUR
TI  - An End-to-End Fault Diagnosis Model for Rolling Bearings Based on Multi-Scale Convolution and the Kolmogorov–Arnold Network
AU  - Donghua Yu
AU  - Zhenyu Wang
AU  - Jia Liu
AU  - Huan Liu
AU  - Changtian Ying
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26134005
UR  - https://doi.org/10.3390/s26134005
ER  - 

APA

Yu, D., Wang, Z., Liu, J., Liu, H., & Ying, C. (2026). An End-to-End Fault Diagnosis Model for Rolling Bearings Based on Multi-Scale Convolution and the Kolmogorov–Arnold Network. Sensors. https://doi.org/10.3390/s26134005

Source records