No. 9

Abstracts. No. 9, 2023 year
Fedosov S.V., Fedoseev V.N., Voronov V.A., Zaitseva I.A. (e-mail:
The effect of heat exchange due to the dynamics of induced currents

A new approach to improving the efficiency of heat transfer based on the dynamics of induced currents is proposed. The principle of operation of the device a device for heating a coolant (water) due to the dynamics of induced currents, which is a promising technology in the field of autonomous heating and hot water supply systems, is considered. In the device under consideration, the main source of thermal energy is eddy currents with a braking effect. The device operates from any drive with any rotation speed, including using renewable energy sources.

Keywords: electromagnetic field, induction, heat exchange, eddy currents, Foucault currents.

Ivashin N.A. (e-mail:
Piezoaccelerometer RDUS2040 for complex testing

Description of construction of piezoaccelerometer for complex (shock and vibration) testing, and its main technical characteristics are presented.

Keywords: piezoaccelerometer, piezoelectric shock transducer, shock and vibration, zeroshift, elastic glue layer, mechanical filter.

Maiorov E.E., Arefiev A.V., Guliyev R.B., Pushkina V.P., Tsygankova G.A. (e-mail:
Refractometric control of lacticinia dry residue composition in real production

This article to the refractometric control of the composition of the dry residue of lacticinia in real production is devoted. The use of refractometric methods and means to obtain high-precision and reliable information about the composition of the substance under study has always been a significant task for the food industry, therefore, the study of the composition of the dry residue of lacticinia in real production by refractometry is promising and relevant. The paper the method of the object of research and sets the task are defined. The appearance, optical scheme, and technical characteristics of the refractometer are given. The concentration of dry milk residue from the refractive index was measured at the concentration of dry residue: k = 0,5 %, k = 1 %, k = 1,5 %, k = 2 %, k = 2,5 %. The graphical dependences of the refractive index on temperature with a concentration of dry matter k = 2,5 % for the studied samples are obtained. Experimental results with an error Δn = ± 0,0001 in the temperature range t = 1040 were obtained.

Keywords: refractometer, refractive index, dispersion, measurement error, prism, light scattering, absorption.

Biryukov S.V., Tyukina L.V., Tyukin A.V. (e-mail:
A method for measuring the electric field strength, which allows determining the error from the inhomogeneity of the field and the distance to its source

A new method of measuring the electric field strength using a dual sensor is considered. The method allows you to measure not only the value of the electric field strength, but also to determine its error, and the distance from the center of the sensor to the field source. The operability of the method is confirmed by numerical experiment. The experiment showed that the deviation of the error obtained from the theoretical and empirical values obtained in the numerical experiment does not exceed 5 % on average, and the deviation of the theoretical distance value from the distance value obtained empirically in the numerical experiment does not exceed 6 %. The possibility of a method to additionally determine the error and distance to the field source is being considered for the first time.

Keywords: measurement method, electric field strength, sensor, dual sensor, measurement error, distance to the field source.

Shchepetov A.G., Shimereva L.V. (e-mail:
About problems of analysis, synthesis and optimization of devices

The features of the formulation and solution of problems of analysis, synthesis and optimization of the characteristics of measuring instruments are considered.

Keywords: analysis, synthesis, optimization.

Siddikov I.Kh., Porubay O.V. (e-mail:
Neuro-analytical system for optimization of power flow processes in electric power industry facilities

The article deals with the issue of improving the quality of functioning of the neuro-analytical system for optimizing the processes of power flows in electric power industry facilities. The system analysis of the current state of power supply systems is carried out, based on which the methods of application of neuro-analytical network combining the Mamdani algorithm and recurrent neural network are proposed. To solve the problem, an optimization model based on the criterion of minimum power losses in the distribution elements of electric power systems is proposed. The proposed combined regulator allows to solve both the problem of optimization of operation modes of electric power facilities and to ensure the prevention of emergencies by assessing the load of power distribution nodes.

Keywords: neuro-analytical system, power flow, electric power object, Mamdani algorithm, recurrent neural network, optimization model, minimum criterion, optimization.

Yujra Rivas E., Gogolinskiy K.V. (e-mail:
Algorithm for detecting outliers in large arrays of measurement results (data) using statistical methods of analysis

This paper presents an outlier elimination and smoothing algorithm in measurement data. The outlier elimination process includes an initial cut-off process, an outlier detection process using a modified Z-score based on median absolute deviation (MAD) and an exponentially weighted moving average (EWMA) method is applied to smooth the processed data. The results show that it is necessary to properly determine the value of β and αto eliminate outliers in the measurement data and reduce the standard deviation caused by random errors. Testing and trials of the algorithm on data modeled from the results of the bilateral comparison between the metrological institutes VNIIM and PTB showed that the developed algorithm can be applied to process big data sets, since it is very stable and does not require large computational effort.

Keywords: data smoothing, exponentially weighted moving average, mean absolute deviation, modified Z-score, outlier detection, SPRT.

Sayfutdinov Z.G., Bashmakov D.A., Ilin V.I. (e-mail:
Electrical cable monitoring and diagnostics system

This article discusses the technical diagnostics of the working condition of electrical wiring. Currently, wires and cables are tested with increased voltage and insulation resistance measurements, which is not a way to diagnose the condition of a cable line in real time. The aim of the work is to develop an effective method for detecting cable line damage. In the work, an experimental study was carried out and the results of assessing the current state of electrical wires with insulation were obtained. A new method for diagnosing and monitoring the working condition of electrical wiring has been developed. The implementation of the diagnostic and monitoring method is carried out using inductively coupled elements assembled into an oscillatory circuit. The cable, in turn, acts as the core of the inductors. A change in current in an electrical circuit that is in resonance containing these coils reflects a change in the working condition of the cable. The use of the proposed diagnostic method will help to avoid emergency work on the restoration of the electric line by detecting accumulated defects during operation in real time, which will increase the degree of reliability of the power line and will avoid costly repairs of electrical equipment, the malfunction of which may occur due to deviations of the operating wiring condition.

Keywords: electrical wiring, cables, diagnostics of electrical equipment, insulation, inductors, resonance, oscillatory circuit, monitoring, non-destructive testing, testing automation.

Abdulkhamidov A.A. (e-mail:
Performance assessment of a Convolutional Neural Network for cotton classification based on the degree of openness

This article aims to evaluate the performance of Convolutional Neural Networks (CNN) for the task of cotton classification based on the degree of openness. The authors conducted experiments using a CNN model to classify 400 cotton samples into two categories Well-opened cotton and Poorly-opened cotton. The model's performance was assessed using a confusion matrix, which allows for the calculation of various metrics such as accuracy, precision, and recall. The results showed that the model correctly classified over 98 % of the samples, indicating high performance. Precision and recall scores provide a more detailed assessment of the model's performance in classifying each category of cotton. The findings of this study can be used to optimize the CNN model and improve its performance in classifying cotton based on the degree of openness.

Keywords: Convolutional Neural Networks, class-wise accuracy, epoch-wise accuracy, epoch-wise loss, confusion matrix.

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