Home – Home – Jornals – Avtometriya 2025 number 5

The efficiency of using a neural network for detecting "point" objects whose shape is determined by the characteristics of the recording optical-electronic channel in images with a spatially nonstationary background is studied. The training data sets take into account the diversity of background situations and the variability of the shape of the signal from objects due to their movement. The results of detecting objects of different brightness and colors on real background images obtained during observation of the Earth's surface from a geostationary orbit are presented.

Reflectometric measurements of the ice surface conditions of reservoirs in the Krasnoyarsk Krai and the Republic of Khakasia are conducted using radio signals from navigation satellites emitting in the L1 band. During processing of the resultant reflectograms, mathematical processing of the amplitude-time dependencies is applied using the fast Fourier transform method, allowing for the experimental determination of ice cover thicknesses with various macrophysical characteristics.

Functionally defined surfaces with a complex microstructure are offered for realistic scenes. A model based on wave optics is described for visualizing surfaces with microscale roughness, which increase the realism of objects under various observation and lighting conditions because of diffraction and mutual interference. The model includes modeling of light transfer and surface, which serve as its initial data. The diffraction effects taking into account the surface roughness are shown. An approximation of spatial coherence using a Gaussian filter is considered; as a result, it is possible to visualize not only the glare, but also the diffraction of higher orders.

Under fluctuating meteorological parameters of the atmosphere (temperature, humidity, etc.), the infrared image can dynamically change its contrast and brightness characteristics. This leads to the fact that the morphological imaging pattern of the detected object is subject to changes. The main reason is the inhomogeneity of the atmosphere, which affects the propagation of infrared radiation from the source to the thermal camera, as well as the profile of the object, which characterizes its heat distribution in the field of view of the infrared imager. In this paper, we search for stable features of the morphological imaging pattern for automatic pattern recognition in the middle wavelength infrared range (3-5 μm) relative to the weather conditions and object profile. It is shown that the feature of the middle infrared contrast, which is the difference between the warmest elements of the object and the image background, is an invariant characteristic that can be used in automatic target recognition problems. The results of the experiment for vehicles demonstrate the effectiveness of this parameter relative to changing temperature and humidity of the environment. However, the profile of the object can distort the “stability” of the middle infrared contrast due to the geometric arrangement of the heat-carrying vehicle elements.

The problem of estimating the phase coordinates of an object whose motion is described by a system of differential equations is considered. The Kalman filter equations, derived from the solution of the generalized Stratonovich equation in the Gaussian approximation, are used for the estimation. The generalized Stratonovich equation allows one to consider cases where a multidimensional image of the object being observed is used as an observation signal, i.e., a scalar function of an arbitrary number of variables reflecting the specifics of the observation device. It is shown that the dataset from the multiple observation devices used is included into the generalized Stratonovich equation and the Kalman filter equations as an additive combination of the time derivatives of the likelihood functionals of each individual observation device. Moreover, each of these functionals can account for the correlation of observation noise.

Effective elimination of cyber threats involves detecting attacks and taking protective measures in real time based on streaming data, but existing solutions are not always able to process data in this mode. To solve these problems, it is proposed to use the incremental learning method - fuzzy classification and clustering systems of the Angelov-Yager first-order type. The original implementation of the system uses the Cauchy kernel function; the use of alternative kernel functions has not been considered before. An experimental study of alternative kernel functions on cybersecurity data sets is conducted, a statistically significant difference in the accuracy and number of rules in the application of various functions is revealed, and the best kernel functions for individual data sets are identified

Due to its high productivity and demand for products, the oil industry occupies a special place in the modern industry. Increased attention is paid to monitoring its condition and the performance of the exploited areas. Exploration of new fields and drilling of producing wells require a lot of time and financial costs. To reduce them, advanced technologies are currently widely used, including various artificial intelligence methods, for example, to assess the percentage of fractions in the oil flow from the well. The paper presents the results of studying a number of models based on neural networks of different architectures for predicting the flow rate of components of a multiphase flow from a well. To conduct the study, data received from sensors of multiphase flow meters based on a Venturi pipe and an X-ray flow meter are used.

The paper presents the development of an automated control system for the experimental equipment of the station 1-3 "Fast-flowing processes" of the Center for Collective Use "Siberian Ring Photon Source." The architecture of the control system using open software components and protocols is described. Particular attention is paid to the implementation of the engineer's workstation interface as a web application that provides access to the equipment control and configuration. The key software modules of the server and client parts of the web application are considered. The proposed solution ensures scalability, fault tolerance, and uniformity of the software architecture at all levels of the system.

This paper is devoted to the problem of increasing the fault tolerance of control PLC programs developed on the basis of the process-oriented approach. This paper considers the problem of multiple access conflicts that arise in process-oriented programs when implementing mutually exclusive operations on a separate actuator. The causes of such conflicts are analyzed, and a modification of the mathematical model of a process-oriented program is proposed, which allows elimination of such conflicts in a constructive manner. The resolution of the considered class of conflicts, on the one hand, increases the fault tolerance of control programs and, on the other hand, has no side effects, thus, eliminating the need to change the general structure of the program. To implement the modified model, an extension of the syntax of the poST language is proposed.

A constructive method is proposed for the multi-criteria optimization of nonlinear objects in technological thermal physics. It involves the evaluation of the accuracy of approximation to a given temperature state in numerical modeling of thermo-diffusion fields using a uniform metric. It is clear that the structure of the program control is identical to that previously found for linear models of controlled processes. The technology developed in previous works for solving multi-criteria problems in linear systems with distributed parameters is extended to the nonlinear objects under study. This is done under conditions of selecting time-constant values of special control in the corresponding sections. This is quite simple to implement in such an approximation of program control action on digital models of the controlled variable. The capabilities of the proposed approach are illustrated by an example of independent interest: the numerical solution of the problem of optimizing the induction heating process according to three basic indicators of technical and economic efficiency using a specialized electro-thermal model of the temperature field described by nonlinear heat conduction equations.

This paper presents a Brillouin optical time-domain analysis (BOTDA) system based on a self-sweeping laser. The system interrogates a 50 km optical fiber with a frequency error of 1.5 MHz within a 30-second measurement time. Furthermore, it is demonstrated that the sensing range can be extended to 88 km and 96 km using standard and correlation-based signal processing methods, respectively.

An installation based on a Q-switched Cr:Yb:Ho:YSGG (λ = 2.87 μm) 15 mJ, 40 ns laser is described. The installation is intended for laser damage threshold measurements of 3-μm range optical items and other laser -matter interaction experiments. The peculiarities of laser caustic measurements near the focal plane of an ƒ = 50 mm lens with the aid of the scanning knife method for different temporal structures of the radiation pulse are discussed. At the laser beam diameter of »160 μm, the radiation energy density on the surface of the optical item under investigation can be smoothly varied in the range from 1 to 52 J/cm².

The paper presents an approach to controlling surface plasmon polaritons (SPP) by diffraction on acoustic waves. The Bragg diffraction of the SPP on an ultrasonic beam directed along the interface between media, one being an isotropic dielectric, is considered. It is shown that, in addition to the formation of SPP beams of zero and first diffraction orders, the SPP will also be converted into bulk radiation. Formulas for the intensities of SPP beams of zero and first diffraction orders for the main diffraction modes are derived. The proposed method can be used in the development of modern information processing devices, as well as devices for non-destructive testing of the homogeneity of dielectric coatings on metal surfaces.

In this work, we investigate the response time and sensitivity in the visible spectral range of a commercial pyroelectric detector based on the organic crystal tetraaminodiphenyl MG-32 (JSC NSDE Vostok) with a 0.5 mm thick polypropylene input window. The sensor time constant is varied by connecting the capacitance C in the range from 2 nF to 3.8 μF to the feedback circuit of the receiver amplifier. With an increase in the capacitance in the range of 0.1 - 3.8 μF, the receiver time constant increases linearly from 0.2 to 5 ms; at lower capacitances, it reaches saturation, setting a limit of ≈ 25 μs. The voltage sensitivity is tested using diode laser radiation (λ = 637 nm), which at C = 0.1 μF is 3600 V/W, which is 8% smaller than the sensitivity of the receiver without a polypropylene window. The equivalent noise power and detectability are practically independent of the feedback capacitance in the range C = 0.002 - 0.1 μF and are approximately 1-2 orders of magnitude superior to the characteristics of other commercial pyroelectric detectors and the Golay optoacoustic cell in the visible range, which makes the receiver under study quite promising and universal for many applications.