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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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Алгоритм быстрого синтеза Е-импульса

Успехи современной радиоэлектроники. 2016. № 2. С. 48–51.
Филимонова Д. В., Shevgunov T., Ефимов Е. Н.

In this paper, E pulse target discrimination method which uses the time-domain target response to a wideband incident waveform is discussed. Based upon the resonant model of the transient behavior of conducting targets obtained and formularized via the singularity-expansion method (SEM), the E pulse method allows developing the computationally efficient technique for discrimination of radar targets. The E pulse is defined as a finite duration waveform, which annihilates a preselected number of the natural resonances of a particular target. Mathematically, this means the convolution product of the target response and the E pulse matched to the target will vanish in late-time part. The E pulse can be analytically represented as a weighted sum of convenient basis functions. The most useful basis set, due to its great simplicity, is one that is composed of subsectional polynomial pulse functions. Finding the coefficients of polynomials to obtain functions that determine the waveform of E pulse over each of the sections could be ob-tained by solving large-scale system of linear equations with elements evaluated sophisticatedly. In practice, there emerges a chain of difficulties associated with this problem, for example, an ill-conditioned matrix case. The purpose of this work is to introduce an alterna-tive synthesis algorithm of polynomial based E pulses. This multistep algorithm proposes producing an E pulse consisting of delta-functions at the first step, and then, a series of step-by-step cross convolutions up to the desired polynomial degree. Not only does this solution not imply solving any equations but it also requires a great deal few operations than standard equation solving procedure. In addition, the discrimination scheme assembled for this method was investigated. The E pulse technique performance was confirmed by numerical simulation using natural resonances of two aircraft scale models: Boeing 707 (B-707) and McDonnel Douglas F-18.

Research target: Mathematics Electronics and Electrical Engineering
Priority areas: IT and mathematics engineering science
Language: Russian
Text on another site
Keywords: цифровая обработка сигналовdigital signal processingE-pulseгасящий импульссобственные резонансыраспознавание радиолокационных целейultra-wideband radar systemsnatural resonancesextinction pulseradar target discriminationсверхширокополосная радиолокация
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