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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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Evaluation of durability of mineral wool products

Vol. 1077. Advanced Materials, Structures and Mechanical Engineering, 2015.
Zhukov A., Bobrova E., Smirnova T. V.

The durability of building structures is one of the most important requirements of modern construction. The durability of the structure depends on the operational durability of all the materials and elements that make up the structure. The durability of the insulation structure is determined by the preservation of the thermal insulation properties of this structure. The use of methods for assessing the operational stability of insulation materials allows you to get reliable results and save time and resources.

Research target: Construction
Priority areas: engineering science
Language: English
DOI
Keywords: durabilityдолговечностьтехнология теплоизоляционных материалов и бетонов; строительное материа-ловедение; долговечность строительных материалов и строительных систем, защита строительных конструкций от коррозии, компьютерное моделирование технологий строительных материалов и строительных систем.Durability of building structures
Evaluation of durability of mineral wool products
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