NEURAL NET USING TO DETERMINE DEPTH AND FREQUENCY OF SIGNALS’ MODULATION FOR ELECTRICAL EQUIPMENT ULTRASONIC VIBROCONTROL

Anatoly V. Bychkov, Irina Yu. Bychkova, Nadezhda N. Suslova, Kurbangali K. Alimov

DOI: 10.47026/1810-1909-2021-3-21-30

Key words

artificial neural network, vibration control, ultrasonic pulses, electrical equipment.

Abstract

The apparatus of artificial neural networks (ANN) is proposed to be used for signal processing in active ultrasonic (US) vibration control of electrical equipment. A feature of the applied neural network algorithm is that the required information about vibration parameters is embedded in the ultrasound signal’s phase change at its constant amplitude. Under these conditions, traditional spectral analysis of signals requires a high sampling rate and a significant recording duration. When using the direct propagation’s ANN with three hidden layers, it was shown that it is sufficient to use a sampling frequency of 5-6 points for the period of an ultrasonic wave and a recording duration of 4-5 periods to estimate the nonstationary frequency and amplitude of the vibration signal. Estimates of the error in determining the amplitude, frequency and phase of vibrations are obtained. The root-mean-square errors of the neural network algorithm do not exceed units of percent. The possibilities of using a trained neural network for signal processing in a “sliding window” are demonstrated. The accuracy characteristics of the proposed neural network algorithm of signal processing and the possibility of its optimization for electrical equipment’s vibration control are discussed.

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Information about the authors

Anatoly V. Bychkov – Post-Graduate Student of Electrical and Electronic Apparatuses Department, Chuvash State University, Russia, Cheboksary (bav.xlab@gmail.com; ORCID: https://orcid.org/0000-0003-2674-8626).

Irina Yu. Bychkova – Post-Graduate Student, Department of Automation and Control in Technical Systems, Chuvash State University, Russia, Cheboksary (biy.quint@gmail.com; ORCID: https://orcid.org/0000-0001-9852-3288).

Nadezhda N. Suslova – Master’s Program Student, Faculty of Radio Electronics and Automation, Chuvash State University, Russia, Cheboksary (suslova.nadeshda@yandex.ru).

Kurbangali K. Alimov – Candidate of Physical and Mathematical Sciences, Associate Professor of the Department of Applied Physics and Nanotechnology, Chuvash State University, Russia, Cheboksary (alimkur55@mail.ru).

For citations

Bychkov A.V., Bychkova I.Yu., Suslova N.N., Alimov K.K. NEURAL NET USING TO DETERMINE DEPTH AND FREQUENCY OF SIGNALS’ MODULATION FOR ELECTRICAL EQUIPMENT ULTRASONIC VIBROCONTROL. Vestnik Chuvashskogo universiteta, 2021, no. 3, pp. 21–30. DOI: 10.47026/1810-1909-2021-3-21-30 (in Russian).

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