Python Scripts for Wind Turbine Main Bearing Fatigue Life Estimation with Physics-informed Neural Networks

Welcome to the PML repository for physics-informed neural networks used in main bearing prognosis. We will use this repository to disseminate our research in this exciting topic.

In order to run the codes, you will need to install the PINN python package: https://github.com/PML-UCF/pinn.

Citing this repository

Please, cite this repository using:

@misc{2019_yucesan_viana_python_main_bearing,
    author    = {Y. A. Yucesan and F. A. C. Viana},
    title     = {Python Scripts for Wind Turbine Main Bearing Fatigue Life Estimation with Physics-informed Neural Networks},
    month     = Aug,
    year      = 2019,
    doi       = {10.5281/zenodo.3355725},
    version   = {0.0.1},
    publisher = {Zenodo},
    url       = {https://github.com/PML-UCF/pinn_wind_bearing}
    }

The corresponding reference entry should look like this:

Y. A. Yucesan and F. A. C. Viana, Python Scripts for Wind Turbine Main Bearing Fatigue Life Estimation with Physics-informed Neural Networks, v0.0.1, Zenodo, https://github.com/PML-UCF/pinn_wind_bearing, doi:10.5281/zenodo.3355725.

Publications

Over time, the following publications out of the PML-UCF research group used/referred to this repository:

• Y. A. Yucesan and F. A. C. Viana, "A hybrid physics-informed neural network for main bearing fatigue prognosis under grease quality variation," Mechanical Systems and Signal Processing, Vol. 171, pp. 108875, 2022. (DOI: 10.1016/j.ymssp.2022.108875).

• Y. A. Yucesan, A. Dourado, and F. A. C. Viana, "A survey of modeling for prognosis and health management of industrial equipment," Advanced Engineering Informatics, Vol. 50, pp. 101404, 2021. (DOI: 10.1016/j.aei.2021.101404).

• Y. A. Yucesan and F. A. C. Viana, "Hybrid physics-informed neural networks for main bearing fatigue prognosis with visual grease inspection," Computers in Industry, Computers in Industry, Vol. 125, pp. 103386, 2021. (DOI: 10.1016/j.compind.2020.103386).

• F. A. C. Viana, R. G. Nascimento, A. Dourado, and Y. A. Yucesan, "Estimating model inadequacy in ordinary differential equations with physics-informed neural networks," Computers and Structures, Vol. 245, pp. 106458, 2021. (DOI: 10.1016/j.compstruc.2020.106458).

• Y. A. Yucesan and F. A. C. Viana, "A physics-informed neural network for wind turbine main bearing fatigue," International Journal of Prognostics and Health Management, Vol. 11 (1), 2020. (ISSN: 2153-2648).