Research progress on oil-immersed transformer mechanical condition identification based on vibration signals
YT Sun, HZ Ma - Renewable and Sustainable Energy Reviews, 2024 - Elsevier
In recent years, vibration signals have been widely applied for the identification of
mechanical states in oil-immersed transformers. This paper, following the framework of …
mechanical states in oil-immersed transformers. This paper, following the framework of …
Rotor angle stability of a microgrid generator through polynomial approximation based on RFID data collection and deep learning
The article proposes a novel approach to assess rotor angle stability in microgrids by
enhancing the Modified Galerkin Method (MGM), which is based on the Polynomial …
enhancing the Modified Galerkin Method (MGM), which is based on the Polynomial …
The Sustainability Concept: A Review Focusing on Energy
The concept of sustainability, with a focus on energy, has emerged as a central tenet in
addressing the mounting global challenges of environmental degradation and resource …
addressing the mounting global challenges of environmental degradation and resource …
Enhancing wind speed forecasting through synergy of machine learning, singular spectral analysis, and variational mode decomposition
SR Moreno, LO Seman, SF Stefenon… - Energy, 2024 - Elsevier
Due to technological advancements, wind energy has emerged as a prominent renewable
power source. However, the intermittent nature of wind poses challenges in accurately …
power source. However, the intermittent nature of wind poses challenges in accurately …
Video-based human activity recognition using deep learning approaches
Due to its capacity to gather vast, high-level data about human activity from wearable or
stationary sensors, human activity recognition substantially impacts people's day-to-day …
stationary sensors, human activity recognition substantially impacts people's day-to-day …
Group method of data handling using Christiano–Fitzgerald random walk filter for insulator fault prediction
Disruptive failures threaten the reliability of electric supply in power branches, often
indicated by the rise of leakage current in distribution insulators. This paper presents a …
indicated by the rise of leakage current in distribution insulators. This paper presents a …
Evaluation of visible contamination on power grid insulators using convolutional neural networks
The contamination of insulators increases their surface conductivity, resulting in a higher
chance of shutdowns occurring. To measure contamination, equivalent salt deposit density …
chance of shutdowns occurring. To measure contamination, equivalent salt deposit density …
On-machine inspection and compensation for thin-walled parts with sculptured surface considering cutting vibration and probe posture
Y Hao, L Zhu, S Qin, X Pei, T Yan, Q Qin… - … Journal of Extreme …, 2024 - iopscience.iop.org
On-machine inspection has a significant impact on improving high-precision and efficient
machining of sculptured surfaces. Due to the lack of machining information and the inability …
machining of sculptured surfaces. Due to the lack of machining information and the inability …
Hypertuned wavelet convolutional neural network with long short-term memory for time series forecasting in hydroelectric power plants
Energy planning in Brazil is based on assessing the availability of hydrological resources in
the future, thus guaranteeing the supply of energy based on hydroelectric generation …
the future, thus guaranteeing the supply of energy based on hydroelectric generation …
[HTML][HTML] Hypertuned temporal fusion transformer for multi-horizon time series forecasting of dam level in hydroelectric power plants
SF Stefenon, LO Seman, LSA da Silva… - International Journal of …, 2024 - Elsevier
This paper addresses the challenge of predicting dam level rise in hydroelectric power
plants during floods and proposes a solution using an automatic hyperparameters tuning …
plants during floods and proposes a solution using an automatic hyperparameters tuning …