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 …

Parametric and nonparametric machine learning techniques for increasing power system reliability: a review

F Imam, P Musilek, MZ Reformat - Information, 2024 - mdpi.com
Due to aging infrastructure, technical issues, increased demand, and environmental
developments, the reliability of power systems is of paramount importance. Utility companies …

Predictive maintenance for distribution system operators in increasing transformers' reliability

V Vita, G Fotis, V Chobanov, C Pavlatos, V Mladenov - Electronics, 2023 - mdpi.com
Power transformers' reliability is of the highest importance for distribution networks. A
possible failure of them can interrupt the supply to consumers, which will cause …

Applied complex diagnostics and monitoring of special power transformers

G Ivanov, A Spasova, V Mateev, I Marinova - Energies, 2023 - mdpi.com
As a major component in electric power systems, power transformers are one of the most
expensive and important pieces of electrical equipment. The trouble-free operation of power …

Deep learning-based transformer moisture diagnostics using long short-term memory networks

A Vatsa, AS Hati, V Bolshev, A Vinogradov… - Energies, 2023 - mdpi.com
Power transformers play a crucial role in maintaining the stability and reliability of energy
systems. Accurate moisture assessment of transformer oil-paper insulation is critical for …

A systematic literature review on machine learning applications at coal-fired thermal power plants for improved energy efficiency

C Bisset, PVZ Venter, R Coetzer - International Journal of …, 2023 - Taylor & Francis
Power generation comprises high environmental and ecological impacts. The global power
industry is under pressure to develop more efficient ways to operate and reduce the impacts …

Stacked Ensemble Regression Model for Prediction of Furan

MA Faraji, A Shooshtari, A El-Hag - Energies, 2023 - mdpi.com
Furan tests provide a non-intrusive and cost-effective method of estimating the degradation
of paper insulation, which is critical for ensuring the reliability of power grids. However …

[HTML][HTML] Metodología para el mantenimiento predictivo de transformadores de distribución basada en aprendizaje automático

LI Alvarez, CA Lozano, DA Bravo - Ingeniería, 2022 - scielo.org.co
Contexto: En este artículo describimos una metodología ́ıa que se ha establecido para
programar el mantenimiento predictivo de transformadores de distribución en el …

[HTML][HTML] Dataset of audio signals from brushless DC motors for predictive maintenance

RSP Estacio, DAB Montenegro, CFR Rodas - Data in Brief, 2023 - Elsevier
Abstract Predictive Maintenance (PdM) has a main role in the Fourth Industrial Revolution;
its goal is to design models that can safely detect failure in systems before they fail, aiming to …

[PDF][PDF] Application of Tiny Machine Learning in Predicative Maintenance in Industries

SO Ooko, SM Karume - Journal of Computing Theories and …, 2024 - researchgate.net
The advancements in the Internet of Things (IoT) and Machine Learning (ML) have enabled
significant improvements in Predictive Maintenance (PdM) in industries, providing economic …