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[HTML][HTML] A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries
As widely used for secondary energy storage, lithium-ion batteries have become the core
component of the power supply system and accurate remaining useful life prediction is the …
component of the power supply system and accurate remaining useful life prediction is the …
[HTML][HTML] A critical review of improved deep convolutional neural network for multi-timescale state prediction of lithium-ion batteries
Lithium-ion batteries are widely used as effective energy storage and have become the main
component of power supply systems. Accurate battery state prediction is key to ensuring …
component of power supply systems. Accurate battery state prediction is key to ensuring …
[HTML][HTML] Hybrid-YOLO for classification of insulators defects in transmission lines based on UAV
Transmission power lines are essential to supply electrical energy to consumption centers.
Kee** a reliable transmission system requires the early identification of faults. Image …
Kee** a reliable transmission system requires the early identification of faults. Image …
[HTML][HTML] An advanced machine learning based energy management of renewable microgrids considering hybrid electric vehicles' charging demand
Renewable microgrids are new solutions for enhanced security, improved reliability and
boosted power quality and operation in power systems. By deploying different sources of …
boosted power quality and operation in power systems. By deploying different sources of …
Efficient fused-attention model for steel surface defect detection
CC Yeung, KM Lam - IEEE Transactions on Instrumentation …, 2022 - ieeexplore.ieee.org
Steel surface defect detection is an essential quality control task in manufacturing. As
patterns of defects may be viewed as an object, some current defect detection methods …
patterns of defects may be viewed as an object, some current defect detection methods …
Interpretable visual transmission lines inspections using pseudo-prototypical part network
To guarantee the reliability of the electric energy supply, it is necessary that the transmission
lines are operating without interruptions. To improve the identification of faults in the …
lines are operating without interruptions. To improve the identification of faults in the …
[HTML][HTML] Non-intrusive load decomposition based on CNN–LSTM hybrid deep learning model
X Zhou, J Feng, Y Li - Energy Reports, 2021 - Elsevier
With the rapid development of science and technology, the problem of energy load
monitoring and decomposition of electrical equipment has been receiving widespread …
monitoring and decomposition of electrical equipment has been receiving widespread …
Insulator defect detection with deep learning: A survey
Y Liu, D Liu, X Huang, C Li - IET Generation, Transmission & …, 2023 - Wiley Online Library
With the improvement of smart grid, utilizing unmanned aerial vehicles (UAV) to detect the
operation status of insulators has attracted widespread attention. The insulator defects can …
operation status of insulators has attracted widespread attention. The insulator defects can …
Object detection in power line infrastructure: A review of the challenges and solutions
P Sharma, S Saurav, S Singh - Engineering Applications of Artificial …, 2024 - Elsevier
Lack of proper maintenance of power line infrastructures is one of the main reasons behind
power shortages and major blackouts. Current inspection methods are human-dependent …
power shortages and major blackouts. Current inspection methods are human-dependent …
A survey on applications of unmanned aerial vehicles using machine learning
Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including
health, transport, telecommunications and safe and rescue operations. Their adoption can …
health, transport, telecommunications and safe and rescue operations. Their adoption can …