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 …
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 …
developments, the reliability of power systems is of paramount importance. Utility companies …
Predictive maintenance for distribution system operators in increasing transformers' reliability
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 …
possible failure of them can interrupt the supply to consumers, which will cause …
Applied complex diagnostics and monitoring of special power transformers
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 …
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
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 …
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 …
industry is under pressure to develop more efficient ways to operate and reduce the impacts …
Stacked Ensemble Regression Model for Prediction of Furan
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 …
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
Contexto: En este artículo describimos una metodología ́ıa que se ha establecido para
programar el mantenimiento predictivo de transformadores de distribución en el …
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 …
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
The advancements in the Internet of Things (IoT) and Machine Learning (ML) have enabled
significant improvements in Predictive Maintenance (PdM) in industries, providing economic …
significant improvements in Predictive Maintenance (PdM) in industries, providing economic …