The problem of automating the interpretation of remote sensing data from natural objects is considered. It is shown that existing methods for structural analysis of spectral data are based on expert evaluation of the algorithms used. To automate the decoding of remote sensing information, a modifi ed method of structural data analysis has been developed, based on the use of the components of the correlation coeffi cient of a pair of spectral features. Each component is determined by the product of its components in the form of normalized values of spectral features. Based on the signs of the components of the correlation coeffi cient (positive, negative and alternating), four classes are formed. Based on the information obtained, a decision rule is determined for assessing the belonging of a control situation in the space of a pair of spectral features to one of the detected classes. Using the example of detecting forest areas damaged by the Siberian silkmoth, a comparison was made between the results of applying the proposed method and traditional methods of decomposing remote sensing data using normalized vegetation indices NDVI and GNDVI. To characterize the detected classes using the proposed method and to determine the threshold values of NDVI and GNDVI, kernel probability density estimates are used. The procedure for optimizing the kernel probability density estimate is considered, based on the choice of the fuzziness coeffi cients of the kernel functions from the condition of the maximum likelihood function. The use of a modifi ed method of structural analysis of remote sensing data allows us to circumvent the problem of determining threshold values of vegetation indices.

The problem of correcting the dynamic error by restoring the sensor input signal in the presence of additive noise at its output is considered. A review of publications on the application of the Savitzky-Golay fi lter in dynamic measurements is carried out. A block diagram of an adaptive dynamic measuring system based on the discrete Savitzky-Golay differentiating fi lter is developed. For the possibility of using the differentiating fi lter, a method is proposed for reducing the sensor transfer function to a minimum form of an integrating unit, the order of which is equal to the difference in the orders of the denominator and numerator of the sensor transfer function. Reduction is performed by processing a sequence of discrete samples of the sensor output signal using a reduction unit, the output signal of which is equivalent to the output signal of the reduced sensor transfer function. After analyzing the dynamic error of the sensor input signal restoration, an estimate of the error and its components is proposed, due to the difference between the sensor's transfer function and the ideal one and the additive noise at its output. The noise adaptation of the differentiating fi lter parameter is carried out by minimizing the mean square deviation of the dynamic error estimate. A computer simulation of the proposed measuring system is performed in the presence of additive random noise at the output of a second-order sensor. The effectiveness of estimating the dynamic error of reconstructing the sensor input signal based on the structure of a measuring system with the Savitzky-Golay differentiating fi lter is demonstrated. The application fi eld of the measuring system obtained is the measurement data processing of fast-changing quantities such as temperature, pressure, speed and acceleration, when the dynamic component of the error, caused by inertia of the sensor, as well as additive noises at its output, is dominant.

Modern additive technologies, in particular selective laser melting, allow the creation of products with complex geometries and the required physical and mechanical characteristics. The quality of the final product is infl uenced by the composition of the gas environment in the working chamber of selective laser melting installations. The most critical factor is the oxidation of molten metal, which leads to the formation of shape defects and deterioration of the mechanical properties of the finished product. Existing standard monitoring systems based on remote sensors do not provide suffi cient information about the gas environment in the working chamber of the installations, for example, about local fl uctuations in its composition directly in the melt bath and the formation of gaseous oxidants – nitrogen oxides NOx and water vapour. A method for comprehensive monitoring of the gas environment has been proposed and experimentally validated, based on the detection of the total concentration of molecular oxygen, NOx and moisture indicators H2, NH3. The architecture of an information and measurement system for comprehensive monitoring of the gas environment has been developed. The system can be integrated into existing industrial equipment without any design changes. Experimental studies on EOS M 280 (Electro Optical Systems, Germany) and Farsoon FS 121M (Farsoon, China) technological machines have confi rmed the formation of NOx during the melting process and shown that the proposed method can provide more accurate information about the state of the atmosphere than standard systems. The developed information and measurement system for comprehensive monitoring is designed to prevent oxidative processes in the working chamber of a selective laser melting installation by means of multi-level control of the gas environment composition. Automatic gas supply control based on real-time multi-parameter analysis provides a more complete picture of the chemical composition of the environment and allows for an adequate response to oxidation risks, minimising defects and improving product quality.

This article examines the metrological support for wastewater monitoring required to reduce water pollution, from assessing the initial quality of effl uents to monitoring the effectiveness of their treatment before discharge into natural waters. A priority innovative task for water-intensive chemical industries is described: comparing the results of measurements of various parameters of water composition and properties to selectively reduce the concentration of particularly hazardous toxicants. The need to improve the methodology for identifying (and subsequently removing) pollutants that most signifi cantly increase environmentally hazardous chemical and biological oxygen demand is demonstrated. A comparison of metrological analysis methods, such as predictive mathematics, traditional regression analysis, and neural networks, is conducted using the example of a study of wastewater from the sewer system of the Kemerovo Nitrogen Industry Enterprise “AZOT”. Neural networks are shown to be the most effective method, as they have been used to establish the most comprehensive and maximum number of cause-and-effect relationships, including nonlinear ones, between pollutants and chemical and biological oxygen demand, compared to other methods. Based on the results of the study, it is recommended to use neural networks to analyze the cause-and-effect relationships of measured values of the composition and properties of wastewater for metrological support of water and environmental safety of industrial wastewater disposal in nitrogen production.

The state of the reference base, designed to reproduce the unit of torque of force in the range of large values, is analyzed. An analysis of publications on reference installations has confirmed the relevance of developing and implementing high-precision reference installations that reproduce a unit of torque in the range of more than 20 kN·m. To achieve high accuracy of reproducing the unit of torque of the force, special design solutions are used in installations that exclude the infl uence of the parasitic components of the force vector and the radius vector of the shoulder on the measured (reproducible) value – the modulus of the torque vector of the force. In addition, they use expensive materials and place high demands on the precision of manufacturing parts. To successfully solve the problems of creating reference installations reproducing a unit of force torque in the range of more than 20 kN·m, a generalized physical and mathematical model of the force torque measurement process based on the classical defi nition of force torque as the vector product of the force vector and the radius vector of the shoulder has been developed in conditions of limited fi nancial possibilities. The developed generalized physical and mathematical model makes it possible to take into account the infl uence on the measurement results of the design features of measuring installations and methodological and instrumental factors related to the measurement methods of force vectors and the radius vector of the shoulder, as well as the technical means used in reproducing and transmitting the unit of torque of force in accordance with the measurement methods. A preliminary mathematical modeling of the process of reproducing the unit of torque of force has been carried out, and the infl uence of the measurement error of the radius of the shoulder vector and the accuracy of the axis of rotation on the uncertainty of the force torque measurements has been estimated. As a result, the applicability of the developed generalized physical and mathematical model of the process of measuring the torque of a force for estimating the uncertainty of measurements by the Monte Carlo method and determining the requirements for the components of the projected installation is shown. The results obtained make it possible to design installations for reproducing the unit of torque of a force in the range of large values using digital modeling.

The research is aimed at improving the accuracy of non-contact viscosity measurements in conditions of a limited sample volume of a tested liquid. A non-contact aerodynamic method based on the deformation of the liquid surface by a gas jet is considered and makes it possible to measure viscosity directly in a technological apparatus or container with liquid or in any vessel of arbitrary shape, the dimensions of which exceed the minimum allowable. In order to determine the minimum size of the vessel, the effect of distances from the walls and bottom of a rectangular vessel to the area of the impingement of the jet to the tested liquid on the viscosity measurement results was experimentally investigated. The experiments were performed on a pulsed non-contact device with an inclined aerodynamic impingement (a non-contact aerohydrodynamic viscometer). Additional movable walls and a submerged movable bottom were utilized to change the vessel dimensions. Liquids with viscosity of 0.710 Pa·s (castor oil) and 26.1 Pa·s (epoxy resin) at 25 °C were studied. The angles of aerodynamic impingement were 20° and 50°, and the gas pressure in front of the gas jet outlet varied at two levels – 5.4 and 7.0 kPa. The minimum dimensions of the vessel are determined – length 80 mm, width 40 mm, thickness of the liquid layer 20 mm, at which the additional measurement error of viscosity due to the infl uence of the vessel walls does not exceed 1.5 %. The minimum volume of a liquid sample in a rectangular vessel is 64 ml. The results obtained are useful to employees of chemical analysis laboratories in the chemical, petroleum, electrical and food industries.

The article describes the defi ciencies in the fl ow geometry of a typical pressure pipeline system and the layout of a fl owmeter unit used in a verifi cation rig. A signifi cant problem with water fl ow through a complex fl ow section of a pressure pipeline system is fl ow separation at the walls, leading to cavitation and vibrations within the pipeline system. An approach is proposed that eliminates cavitation in the water fl ow and wall vibrations in complex sections of a pressure pipeline system. This is achieved by creating a vortex structure in the water fl ow in the receivers of a fl owmeter unit with passive fl ow swirl. Geometric models of the fl ow sections of pressure pipeline systems and fl owmeter units (typical and prospective with passive fl ow swirl) are constructed. High-resolution grid models with denser near-wall regions adapted for calculations are generated. Dimensionless coordinates (local Reynolds numbers in cells) are determined, which can be used to calculate turbulence models based on averaging the Navier-Stokes equations over the Reynolds number. The results of numerical predictions are verifi ed based on the results of an experimental study of pressure losses in a fl ow meter unit of a typical pipeline system. Numerical modeling of pressure losses in a fl ow meter unit with passive fl ow swirl in a prospective pipeline system was performed, based on which this system was designed, created, and experimentally studied. The quality of the turbulent water fl ow velocity profi le in the outlet cross-section of the prospective pipeline system and the effect of the paired vortex structure in the pressure pipeline on the fl ow structure and the formation of the velocity profi le in the measuring line are assessed. The hydraulic effi ciency of the fl ow meter unit with passive fl ow swirl is substantiated. A pressure single-phase (cavitation-free) water fl ow is implemented. The presented approach and the obtained results can be used in the development of new verifi cation rigs and the modernization of existing ones. Keywords: verifi cation rig, pressure fl ow, fl ow meter block, passive fl ow swirl, velocity profi le, hydraulic effi ciency.

The currently used data on the heat capacity of Bismuth were obtained in the 1980s. Different methods and different measuring equipment were used to obtain these data. The data on heat capacity published in different sources differ by a value greater than the permissible error of the measuring instruments and techniques used. There is no information in the available sources about the applied methods of registration of input data and statistical processing methods. It is impossible to assess the reliability of the Bismuth heat capacity measurements based on this situation. Bismuth in its pure form and in alloys is widely used in industry and engineering. The unreliability of its heat capacity leads to several problems. The fi rst is the lack of reference values for the specifi c heat capacity of Bismuth, which are necessary for the input control of materials in the electrical industry. The second is overestimation of tolerances during design calculations. The third is the reduction of the working ranges of alloys. The article presents the results of a study of the specifi c heat capacity of pure Bismuth in the period 2021–2025. The stability of reproducing the specifi c heat capacity of Bismuth during storage without special conditions and the possibility of using this material to control temperature scales and measuring instruments for thermal analysis are evaluated. The results obtained will be useful to metrologists and users of measuring instruments for complexthermal analysis, materials scientists investigating the thermophysical properties of semi-metals and layered structures, developers of the electrical and instrument engineering industry, technologists of the chemical and pharmaceutical industries

In the context of the current direction of research in the fi eld of acoustic measurements – non-invasive analysis of the voice source – the problem of measuring excitation parameters for a vocoder with linear prediction is considered. The acute problem of high computational complexity of known methods of its solution based on the technique of “analysis by synthesis” is indicated. In order to overcome this problem, a high-speed acoustic measurement method has been developed based on the criterion of the minimum average sample value of the linear prediction error. It is shown that this criterion implements the principle of minimizing the energy consumption of the announcer for the speech production. An example of technical implementing the developed method is considered, and estimates of its computational complexity are given. It is shown that, compared to the well-known method of multi-pulse excitation of a linear prediction vocoder using two address books: adaptive and stochastic, the costs of implementation of the proposed method are reduced by several orders of magnitude. To confi rm this conclusion, a natural experiment was conducted using the author's software on a set of vowel phonemes from a control speaker. It is shown that by optimizing the excitation signal shape, the mean sample value of the linear prediction error is signifi cantly reduced. The obtained results can be useful in developing new and upgrading existing systems and technologies for speech coding and synthesis, mobile speech communication and other applications of digital speech signal processing with data compression based on the linear prediction model.

Рассмотрено повышение точности измерения влажности сыпучих материалов, имеющей критическое значение для обеспечения качества, сохранности продукции и эффективности технологических процессов в сельском хозяйстве, пищевой промышленности и строительстве. Дан краткий обзор методов измерения влажности и показано, что традиционные методы, включая гравиметрический анализ, хотя и отличаются высокой точностью, не обеспечивают оперативный и непрерывный контроль. Разработанметод измерения влажности с использованиемизмерительной системы, состоящей из сенсорной и интеллектуальной частей. Сенсорная часть – влагомер, содержащий ёмкостные датчики, регистрирует диэлектрическую проницаемость материала, сигналы датчиков поступают в блок сбора и предварительной обработки, где выполняется фильтрация и нормализация данных. Сенсорная часть обеспечивает стабильные измерения влажности пшеницы, кукурузы и песка в диапазоне 6–25 %. Интеллектуальная часть системы включает регрессионную модель, которая учитывает влияние диэлектрической проницаемости, объёмной плотности материала и температуры окружающей среды на точность измерений влажности и представляет собой многопараметрическую линейную модель, реализованную с помощью библиотеки scikit-learn (Python). Для оценки устойчивости модели применена десятикратная перекрёстная проверка. При экспериментальных исследованиях получены средняя абсолютная погрешность измерения влажности менее 1,8 % и коэффициент детерминации более 0,89, что подтверждает стабильность и воспроизводимость системы. Представленный подход демонстрирует, что интеграция ёмкостных сенсорных систем с интеллектуальными системами на основе регрессионных моделей позволяет повысить надёжность контроля и автоматизировать мониторинг влажности в производственных условиях. Разработанный метод измерения влажности и реализующую его систему можно адаптировать для различных сыпучих материалов и технологических сред.

Digital micromirror devices are widely used for optical processing of graphic information, including for the purpose of building holographic display systems and adaptive formation of light beams. Modulators are also used in the creation of diffraction neuron-like systems. The demand for modulators of this type is due to the unique combination of high switching speed and high spatial resolution for optical systems. This paper presents the results of an experimental study of the HDSLM54D67 digital micromirror device (UPO Labs, China), which, according to the manufacturer, has advanced characteristics for its type. The true values of its spatial and velocity parameters are estimated by displaying binary computer-synthesized Fourier holograms and two-dimensional distributions in the form of geometric primitives. The results revealed an abnormal modulation of the left half of the micromirror matrix, leading to a parasitic doubling of the images reconstructed from the holograms. The analysis of the causes of these distortions was carried out, and their connection with the features of the modulator control unit was revealed. The limitations of the applicability of this digital micromirror device model are determined in accordance with the identifi ed spatial limitations (using only the half of the micromirror matrix with a resolution of 1358×1600 pixels) and proposals for optimal integration of the modulator into an optical system are formulated. The use of a modulator is possible, but theoretically the maximum bandwidth will be reduced by 2 times. The results of the study can be used in further optical experiments with this digital micromirror device, including for the task of constructing a diffraction neural network.

A brief overview of the transformation of the term “uncertainty of the measurement result” in Russian metrology over the past three decades is given, leading to the statement: “The probability distribution fully describes the probabilistic properties of the uncertainty of the result”. It is shown that the concept of error and true value is based on unknown quantities, while the concept of uncertainty operates with unknown probability distributions. It is proposed to understand the error of the measurement object model as a generally uncertain value that characterizes the distribution of possible deviations from the systematic component of the model, taking into account the unobservable components of parametric and nonparametric inadequacy. The mathematical basis for this representation of accuracy in solving measurement problems is the conversion formula, which is a convolution of the probability distributions of the corresponding components of inadequacy.