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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
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Implementation of Bug1 and Bug2 Basic Path-Planning Algorithms for a TurtleBot 3 Robot in ROS Noetic

P. 272–275.
Spektor I., Zagirov A., Safin R., Magid E.
Language: English
DOI
Keywords: ROSnavigationpath planningmobile robotsGazeboBUG Algorithms

In book

Proceedings Of The 2024 International Conference On Artificial Life And Robotics February 22 To 25, 2024 J:Com Horutohall, Oita, Japan. 29Th Arob International Meeting Series
ALife Robotics Corporation Ltd., 2024.
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