Critical wind turbine components prognostics: A comprehensive review
M Rezamand, M Kordestani… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
As wind energy is becoming a significant utility source, minimizing the operation and
maintenance (O&M) expenses has raised a crucial issue to make wind energy competitive to …
maintenance (O&M) expenses has raised a crucial issue to make wind energy competitive to …
A review of research on wind turbine bearings' failure analysis and fault diagnosis
H Peng, H Zhang, Y Fan, L Shangguan, Y Yang - Lubricants, 2022 - mdpi.com
Bearings are crucial components that decide whether or not a wind turbine can work
smoothly and that have a significant impact on the transmission efficiency and stability of the …
smoothly and that have a significant impact on the transmission efficiency and stability of the …
[HTML][HTML] Online condition monitoring of floating wind turbines drivetrain by means of digital twin
FK Moghadam, AR Nejad - Mechanical Systems and Signal Processing, 2022 - Elsevier
This paper presents a digital twin (DT) condition monitoring approach for drivetrains on
floating offshore wind turbines. Digital twin in this context consists of torsional dynamic …
floating offshore wind turbines. Digital twin in this context consists of torsional dynamic …
Fault detection in gears using fault samples enlarged by a combination of numerical simulation and a generative adversarial network
Y Gao, X Liu, J Xiang - IEEE/ASME Transactions on …, 2021 - ieeexplore.ieee.org
It is inevitable for gear to become damaged, which has a profound effect on the performance
of gear transmission systems. Solving the problem of gear fault detection using artificial …
of gear transmission systems. Solving the problem of gear fault detection using artificial …
Wavelet packet decomposition-based multiscale CNN for fault diagnosis of wind turbine gearbox
This article presents an intelligent fault diagnosis method for wind turbine (WT) gearbox by
using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration …
using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration …
Unsupervised health indicator construction by a novel degradation-trend-constrained variational autoencoder and its applications
Health indicator (HI) affects the accuracy and reliability of the remaining useful life (RUL)
prediction model. The hidden variables of variational autoencoder (VAE) can represent the …
prediction model. The hidden variables of variational autoencoder (VAE) can represent the …
A self-data-driven method for remaining useful life prediction of wind turbines considering continuously varying speeds
Predictive maintenance is one of the most promising ways to reduce the operation and
maintenance (O&M) costs of wind turbines (WTs). Remaining useful life (RUL) prediction is …
maintenance (O&M) costs of wind turbines (WTs). Remaining useful life (RUL) prediction is …
Artificial intelligence enhanced two-stage hybrid fault prognosis methodology of PMSM
Fault prognosis based on single model is generally inaccurate due to the varying working
conditions. A multistage fault prognosis methodology combining stage identification with …
conditions. A multistage fault prognosis methodology combining stage identification with …
Wind turbine main bearing fault prognosis based solely on scada data
As stated by the European Academy of Wind Energy (EAWE), the wind industry has
identified main bearing failures as a critical issue in terms of increasing wind turbine …
identified main bearing failures as a critical issue in terms of increasing wind turbine …
Multi-feature fusion approach for epileptic seizure detection from EEG signals
In this article, a new fusion scheme based on the Dempster-Shafer Evidence Theory (DSET)
is introduced for Epileptic Seizure Detection (ESD) in brain disorders. Firstly, various …
is introduced for Epileptic Seizure Detection (ESD) in brain disorders. Firstly, various …