Machine learning applications in health monitoring of renewable energy systems
Rapidly evolving renewable energy generation technologies and the ever-increasing scale
of renewable energy installations are driving the need for more accurate, faster, and smarter …
of renewable energy installations are driving the need for more accurate, faster, and smarter …
[HTML][HTML] Deep learning-based modeling method for probabilistic LCF life prediction of turbine blisk
Turbine blisk is one of the typical components of gas turbine engines. The fatigue life of
turbine blisk directly affects the reliability and safety of both turbine blisk and aeroengine …
turbine blisk directly affects the reliability and safety of both turbine blisk and aeroengine …
Spatio-temporal fusion neural network for multi-class fault diagnosis of wind turbines based on SCADA data
Numerous sensors have been deployed in different locations in components of wind
turbines to continuously monitor the health status of the turbine system and accordingly …
turbines to continuously monitor the health status of the turbine system and accordingly …
A review of fault diagnosis and prediction methods for wind turbine pitch systems
J Lan, N Chen, H Li, X Wang - International Journal of Green …, 2024 - Taylor & Francis
Pitch system is an essential subsystem of a wind turbine, which is to efficiently capture and
maximize the utilization of wind energy by controlling the rotation of the blades. Its safety and …
maximize the utilization of wind energy by controlling the rotation of the blades. Its safety and …
Implementation of digital twins for electrical energy conversion systems in selected case studies
Reference implementation of Digital Twins for electrical energy conversion systems is an
important and open question in the industrial domain. Digital Twins can predict the future …
important and open question in the industrial domain. Digital Twins can predict the future …
Detection of mass imbalance in the rotor of wind turbines using Support Vector Machine
Condition monitoring systems (CMS) are essential to reduce costs in the wind energy sector.
This paper proposes a method based on Support Vector Machine (SVM) to detect rotor mass …
This paper proposes a method based on Support Vector Machine (SVM) to detect rotor mass …
Wind turbine fault detection with multimodule feature extraction network and adaptive strategy
Unexpected failures in wind turbines (WTs) lead to tremendous economic losses and safety
hazards to wind farms. Intelligent condition monitoring and fault detection can prevent …
hazards to wind farms. Intelligent condition monitoring and fault detection can prevent …
The potentiality of integrating model-based residuals and machine-learning classifiers: An induction motor fault diagnosis case
W Purbowaskito, C Lan, K Fuh - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
In the recent development of induction motors fault diagnosis, machine-learning algorithms
have been implemented to replace the need for experts in fault diagnostic decisions. In …
have been implemented to replace the need for experts in fault diagnostic decisions. In …
Randomization-based neural networks for image-based wind turbine fault diagnosis
J Wang, Y Yang, N Li - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
As the development of wind energy industry, the safe production of wind farms has become
an urgent problem. To avoid serious faults and deterioration, building effective diagnostic …
an urgent problem. To avoid serious faults and deterioration, building effective diagnostic …
Remote monitoring and diagnostics of pitch-bearing defects in an MW-scale wind turbine using pitch symmetrical-component analysis
Recently, multiple wind turbine failure databases have reviewed that the pitch system is one
of the subassemblies with the highest failure rates and largest contributors to the overall …
of the subassemblies with the highest failure rates and largest contributors to the overall …