[HTML][HTML] Machine learning methods for wind turbine condition monitoring: A review
This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …
used for condition monitoring in wind turbines (eg blade fault detection or generator …
An overview on fault diagnosis, prognosis and resilient control for wind turbine systems
Z Gao, X Liu - Processes, 2021 - mdpi.com
Wind energy is contributing to more and more portions in the world energy market. However,
one deterrent to even greater investment in wind energy is the considerable failure rate of …
one deterrent to even greater investment in wind energy is the considerable failure rate of …
Fault detection of wind turbine based on SCADA data analysis using CNN and LSTM with attention mechanism
L **ang, P Wang, X Yang, A Hu, H Su - Measurement, 2021 - Elsevier
The complex and changeable working environment of wind turbine often challenges the
condition monitoring and fault detection. In this paper, a new method is proposed for fault …
condition monitoring and fault detection. In this paper, a new method is proposed for fault …
Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks
L **ang, X Yang, A Hu, H Su, P Wang - Applied Energy, 2022 - Elsevier
Renewable energy is widely applied in the world. The key problem of wind energy
application is to improve the reliability of wind turbine and reduce its downtime. Supervisory …
application is to improve the reliability of wind turbine and reduce its downtime. Supervisory …
Non-destructive techniques for the condition and structural health monitoring of wind turbines: A literature review of the last 20 years
A complete surveillance strategy for wind turbines requires both the condition monitoring
(CM) of their mechanical components and the structural health monitoring (SHM) of their …
(CM) of their mechanical components and the structural health monitoring (SHM) of their …
Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications
Condition-based maintenance via vibration signal processing plays an important role to
reduce unscheduled machine downtime and avoid catastrophic accidents in industrial …
reduce unscheduled machine downtime and avoid catastrophic accidents in industrial …
A new statistical features based approach for bearing fault diagnosis using vibration signals
In condition based maintenance, different signal processing techniques are used to sense
the faults through the vibration and acoustic emission signals, received from the machinery …
the faults through the vibration and acoustic emission signals, received from the machinery …
Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects
Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …
identifying potential equipment failures in advance, reducing downtime, and increasing the …
A survey on wind turbine condition monitoring and fault diagnosis—Part II: Signals and signal processing methods
W Qiao, D Lu - IEEE Transactions on Industrial Electronics, 2015 - ieeexplore.ieee.org
This paper provides a comprehensive survey on the state-of-the-art condition monitoring
and fault diagnostic technologies for wind turbines. The Part II of this survey focuses on the …
and fault diagnostic technologies for wind turbines. The Part II of this survey focuses on the …
Wind turbine fault detection using a denoising autoencoder with temporal information
Data-driven approaches have gained increasing interests in the fault detection of wind
turbines (WTs) due to the difficulty in system modeling and the availability of sensor data …
turbines (WTs) due to the difficulty in system modeling and the availability of sensor data …