Enhancing hydroelectric inflow prediction in the Brazilian power system: A comparative analysis of machine learning models and hyperparameter optimization for …

EC da Silva, EC Finardi, SF Stefenon - Electric Power Systems Research, 2024‏ - Elsevier
Electricity generation in Brazil heavily depends on hydroelectric power, making it vulnerable
to fluctuations due to its reliance on weather patterns. Accurately forecasting water inflow …

Multi-scale split dual calibration network with periodic information for interpretable fault diagnosis of rotating machinery

Y Chen, D Zhang, H Ni, J Cheng, HR Karimi - Engineering Applications of …, 2023‏ - Elsevier
Conventional intelligent fault diagnosis algorithms based on signal processing and pattern
recognition have high demands on expert experience and poor generalization performance …

Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods

AU Rehman, W Jiao, Y Jiang, J Wei, M Sohaib… - Applied Soft …, 2025‏ - Elsevier
The review provides an overview of the state-of-the-art in Deep Learning (DL) algorithms for
rolling bearing fault classification which remains vital in industrial sectors including …

[HTML][HTML] A communication-less islanding detection scheme for hybrid distributed generation systems using recurrent neural network

A Hussain, A Mehdi, CH Kim - International Journal of Electrical Power & …, 2024‏ - Elsevier
The proposed scheme in this research paper is a communication-less islanding detection
system based on recurrent neural network (RNN) for hybrid distributed generator (DG) …

A cross-domain intelligent fault diagnosis method based on deep subdomain adaptation for few-shot fault diagnosis

B Wang, M Zhang, H Xu, C Wang, W Yang - Applied Intelligence, 2023‏ - Springer
Most existing cross-domain intelligent fault diagnosis algorithms rely on many samples and
only consider the global alignment of all faults. It is not practical to obtain numerous fault …

Semantic segmentation-based intelligent threshold-free feeder detection method for single-phase ground fault in distribution networks

C Hong, HY Qiu, JH Gao, S Lin… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Feeder detection for single-phase ground fault (SPGF) is challenging in a resonant
grounded system due to the difference in feeder capacitance to ground and the influence of …

Faulty-feeder detection for single phase-to-ground faults in distribution networks based on waveform encoding and waveform segmentation

J Yuan, Z Jiao - IEEE Transactions on Smart Grid, 2023‏ - ieeexplore.ieee.org
Faulty feeder detection helps ensure the stability and safety of power grids after single-
phase-to-ground (SPG) faults occur in distribution networks. The existing detection …

Fault diagnosis of highway machinery hydraulic system based on LS-TF

M Wang, Y Wan, X Liang, X He… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Fault diagnosis of hydraulic system is of great significance to reduce the risk of damage to
road machinery and improve construction safety. The hydraulic system of highway …

High impedance fault classification in microgrids using a transformer-based model with time series harmonic synchrophasors under data quality issues

DAG Cieslak, M Moreto, AE Lazzaretti… - Neural Computing and …, 2024‏ - dl.acm.org
Recent advances in distribution networks, driven by the integration of renewable energy
sources, have spurred the emergence of microgrids, elevating concerns regarded reliability …

[HTML][HTML] Faulty feeder selection based on improved Hough transform in resonant grounded distribution networks

X Wang, X Qu, L Guo, Z Zhang, Y Wang… - International Journal of …, 2024‏ - Elsevier
Due to the weak fault characteristics and inaccurate fault line selection during high
impedance faults, this paper proposes a new method for fault line selection in resonant …