Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources
The integration of renewable energy sources (RESs) has become more attractive to provide
electricity to rural and remote areas, which increases the reliability and sustainability of the …
electricity to rural and remote areas, which increases the reliability and sustainability of the …
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 …
Attention-guided joint learning CNN with noise robustness for bearing fault diagnosis and vibration signal denoising
Mechanical system usually operates in harsh environments, and the monitored vibration
signal faces substantial noise interference, which brings great challenges to the robust fault …
signal faces substantial noise interference, which brings great challenges to the robust fault …
An automatic plant leaf disease identification using DenseNet-121 architecture with a mutation-based henry gas solubility optimization algorithm
S Nandhini, K Ashokkumar - Neural Computing and Applications, 2022 - Springer
Farmers are struggling to provide the fast-growing population with sufficient agricultural
products, while plant diseases result in devastating food loss. The billions of dollars spent by …
products, while plant diseases result in devastating food loss. The billions of dollars spent by …
[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 …
A novel intelligent fault diagnosis method of rotating machinery based on signal-to-image mapping and deep Gabor convolutional adaptive pooling network
W Li, Z Shang, S Qian, B Zhang, J Zhang… - Expert Systems with …, 2022 - Elsevier
To address the limitations of insufficient feature representation and easy to be overwhelmed
by strong noise in the grayscale images of vibration signals, the random generation and …
by strong noise in the grayscale images of vibration signals, the random generation and …
Robust intelligent fault diagnosis strategy using Kalman observers and neuro-fuzzy systems for a wind turbine benchmark
A wind turbine (WT) is an electromechanical system that often operates under a wide range
of production conditions. These electrical systems are nowadays expanding rapidly, and …
of production conditions. These electrical systems are nowadays expanding rapidly, and …
Advances in fault condition monitoring for solar photovoltaic and wind turbine energy generation: A review
Renewable energy-based power generation technologies are becoming more and more
popular since they represent alternative solutions to the recent economic and environmental …
popular since they represent alternative solutions to the recent economic and environmental …
A deep reinforcement transfer convolutional neural network for rolling bearing fault diagnosis
Z Wu, H Jiang, S Liu, R Wang - ISA transactions, 2022 - Elsevier
Deep neural networks highly depend on substantial labeled samples when identifying
bearing fault. However, in some practical situations, it is very difficult to collect sufficient …
bearing fault. However, in some practical situations, it is very difficult to collect sufficient …
Fault diagnosis in wind turbines based on ANFIS and Takagi–Sugeno interval observers
Wind turbine power generation is becoming one of the most critical renewable energy
sources. As wind power grows, there is a need for better monitoring and diagnostic …
sources. As wind power grows, there is a need for better monitoring and diagnostic …