[HTML][HTML] A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries

S Wang, S **, D Bai, Y Fan, H Shi, C Fernandez - Energy Reports, 2021 - Elsevier
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 …

[HTML][HTML] A critical review of improved deep convolutional neural network for multi-timescale state prediction of lithium-ion batteries

S Wang, P Ren, P Takyi-Aninakwa, S **, C Fernandez - Energies, 2022 - mdpi.com
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 …

[HTML][HTML] Hybrid-YOLO for classification of insulators defects in transmission lines based on UAV

BJ Souza, SF Stefenon, G Singh, RZ Freire - International Journal of …, 2023 - Elsevier
Transmission power lines are essential to supply electrical energy to consumption centers.
Kee** a reliable transmission system requires the early identification of faults. Image …

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 …

Interpretable visual transmission lines inspections using pseudo-prototypical part network

G Singh, SF Stefenon, KC Yow - Machine Vision and Applications, 2023 - Springer
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 …

[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 …

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 …

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 …

A survey on applications of unmanned aerial vehicles using machine learning

K Teixeira, G Miguel, HS Silva, F Madeiro - IEEE Access, 2023 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including
health, transport, telecommunications and safe and rescue operations. Their adoption can …