[HTML][HTML] Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing
In metal additive manufacturing (AM), the material microstructure and part geometry are
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
A Review of Data-Driven Solutions to Power Up Maintenance of Electrical Systems for Predictive Decision Making Through Fault Analysis
N Laiton, V Sicachá, AM Garzón… - 2023 IEEE Industry …, 2023 - ieeexplore.ieee.org
The increasing complexity of smart industrial power systems necessitates the use of
advanced data analytics to enable proactive and predictive maintenance. This paper …
advanced data analytics to enable proactive and predictive maintenance. This paper …
Application of Machine Learning Algorithms for Enhanced Smart Grid Control and Management
HM Khounsari, A Fazeli - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
This paper presents an in-depth exploration of machine learning (ML) applications in smart
grids, focusing on six key areas: demand forecasting, energy management, microgrid …
grids, focusing on six key areas: demand forecasting, energy management, microgrid …
Robotic Complex for Assessing the Condition of Electrical Equipment of Substations
A Sabitov, N Gubarev - 2024 International Russian Smart …, 2024 - ieeexplore.ieee.org
This article describes the development and testing of a robotic complex for automating the
processes of thermal imaging and visual inspection of electrical equipment of electrical …
processes of thermal imaging and visual inspection of electrical equipment of electrical …