Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework.

Kamat P, Kumar S, Patil S, Kotecha K

DOI: 10.1016/j.mex.2024.102555
Published: 2024 Jun
Container: MethodsX
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1016/j.mex.2024.102555,
  title = {Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework.},
  author = {Kamat P and Kumar S and Patil S and Kotecha K},
  year = {2024},
  journal = {MethodsX},
  doi = {10.1016/j.mex.2024.102555},
  url = {https://doi.org/10.1016/j.mex.2024.102555}
}

RIS

TY  - JOUR
TI  - Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework.
AU  - Kamat P
AU  - Kumar S
AU  - Patil S
AU  - Kotecha K
PY  - 2024
JO  - MethodsX
DO  - 10.1016/j.mex.2024.102555
UR  - https://doi.org/10.1016/j.mex.2024.102555
ER  -

APA

P, K., S, K., S, P., & K, K. (2024). Anomaly-informed remaining useful life estimation (AIRULE) of bearing machinery using deep learning framework.. MethodsX. https://doi.org/10.1016/j.mex.2024.102555

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pubmed · retrieved 2026-09-25T13:25:10.282Z