Page 14: Research news on AI-enabled digital twins

AI-enabled digital twins combine high-fidelity virtual replicas of physical assets with machine learning and sensing technologies to monitor condition, predict failures, and support operational decision-making. Applications span bridges, railways, nuclear reactors, wind turbines, manufacturing equipment, and urban infrastructure, integrating structural health monitoring, non-destructive evaluation, and high-resolution imaging. Data-driven models enable real-time fault diagnosis, risk-informed maintenance, and optimization of performance, often incorporating robotics, remote sensing, and time-series domain adaptation for robust, continuous infrastructure management.

Engineering

Remote detection system developed for wind turbine blade damage

Maintaining wind turbines and identifying potential vulnerabilities is expensive and time-consuming, especially when they are located offshore. As a result, rotor blades are often simply replaced, a costly process when damage ...

page 14 from 20