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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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Technology measurement in statistics and beyond: reviving technological innovation concept

P. 240–258.
Gokhberg L., Fursov K., Roud V.
Language: English
DOI
Keywords: technology statisticsadvanced manufacturing technology

In book

Handbook of Innovation Indicators and Measurement, 2nd edition
Abdrakhmanova G., Arundel A., De Fuentes C., de Jong P. J., De Marchi, V., Gokhberg L., Roud V., Streltsova E., Vishnevskiy K. Edward Elgar Publishing, 2023.
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The technological foresight plays a significant role in promotion of the emerging technologies. The paper investigates technological prospects of priorities implementation indicated in the ‘Strategy for the Scientific and Technological Development of the Russian Federation’. More precisely, we examine the advanced digital and intelligent production technologies deployment by applying foresight methods and new solutions such ...
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