A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings
Large-scale wind turbine bearings including main bearings, gearbox bearings, generator
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
Review on monitoring, operation and maintenance of smart offshore wind farms
L Kou, Y Li, F Zhang, X Gong, Y Hu, Q Yuan, W Ke - Sensors, 2022 - mdpi.com
In recent years, with the development of wind energy, the number and scale of wind farms
have been developing rapidly. Since offshore wind farms have the advantages of stable …
have been developing rapidly. Since offshore wind farms have the advantages of stable …
Multiscale kernel based residual convolutional neural network for motor fault diagnosis under nonstationary conditions
Motor fault diagnosis is imperative to enhance the reliability and security of industrial
systems. However, since motors are often operated under nonstationary conditions, the high …
systems. However, since motors are often operated under nonstationary conditions, the high …
Fault diagnosis of bearing in wind turbine gearbox under actual operating conditions driven by limited data with noise labels
N Huang, Q Chen, G Cai, D Xu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The fault characteristics of the rolling bearings of wind turbine gearboxes are unstable under
actual operating conditions. Problems such as inadequate fault sample data, imbalanced …
actual operating conditions. Problems such as inadequate fault sample data, imbalanced …
Fault diagnosis of rolling bearing of wind turbines based on the variational mode decomposition and deep convolutional neural networks
Abstract Machine learning techniques have been successfully applied in intelligent fault
diagnosis of rolling bearings in recent years. However, in the real world industrial …
diagnosis of rolling bearings in recent years. However, in the real world industrial …
Simultaneous bearing fault recognition and remaining useful life prediction using joint-loss convolutional neural network
Fault diagnosis and remaining useful life (RUL) prediction are always two major issues in
modern industrial systems, which are usually regarded as two separated tasks to make the …
modern industrial systems, which are usually regarded as two separated tasks to make the …
Rotating machinery fault diagnosis under time-varying speeds: A review
D Liu, L Cui, H Wang - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Rotating machinery often works under time-varying speeds, and nonstationary conditions
and harsh environments make its key parts, such as rolling bearings and gears, prone to …
and harsh environments make its key parts, such as rolling bearings and gears, prone to …
Wind turbine gearbox failure detection based on SCADA data: A deep learning-based approach
Gearbox failure is one of top-ranked factors leading to the unavailability of wind turbines
(WTs). Existing data-driven studies of gearbox failure detection (GFD) focus on improving …
(WTs). Existing data-driven studies of gearbox failure detection (GFD) focus on improving …
Fault diagnosis of industrial wind turbine blade bearing using acoustic emission analysis
Wind turbine blade bearings are often operated in harsh circumstances, which may easily
be damaged causing the turbine to lose control and to further result in the reduction of …
be damaged causing the turbine to lose control and to further result in the reduction of …
DeepFedWT: A federated deep learning framework for fault detection of wind turbines
Data-driven fault detection of wind turbines has gained increasingly attention. Currently,
most existing methods require sufficient labeled data to train a reliable model in a …
most existing methods require sufficient labeled data to train a reliable model in a …