Radiotekhnika

Assessment of the effectiveness of international standards and regulatory acts governing artificial intelligence models for Ukraine

2026-01-19T11:53:06+02:00

The article presents a comprehensive study of the effectiveness of international standards and regulatory acts in the field of artificial intelligence (AI) with the aim of determining the most appropriate model for their implementation in Ukraine. The aim of the work is to conduct a comparative assessment of the leading approaches to AI regulation developed in the EU, the US, Canada, the UK, South Korea, China and other countries, as well as recognised international ISO/IEC standards. The study is based on the comprehensive use of multi-criteria analysis methods: pairwise comparisons, determination of weight coefficients on the Fishburn scale, ranking methods, scoring and numerical evaluation. The assessment was carried out using a system of unconditional and conditional criteria, including validity, flexibility, ethics, complexity, progressiveness, level of transparency of algorithms, prospects for integration, availability of institutional support, and impact on innovative development. The use of the MathCad environment allowed for mathematical modelling and calculation of integral performance indicators.

The results showed that the most balanced and promising for implementation in Ukraine are the European approach (EU AI Act) and the Canadian approach (AIDA), which demonstrate a high level of regulatory maturity, transparency of regulatory procedures, the presence of an ethical component, and effective institutional support. The American approach (NIST AI RMF) and the ISO/IEC 23894 standard took intermediate positions due to their versatility and flexibility. In contrast, the Chinese model showed the lowest adaptability to Ukrainian conditions due to the dominance of centralised control principles. The proposed assessment methodology can be used to develop a national AI regulation strategy in Ukraine aimed at ensuring a balance between security, ethics and innovative technological development.

Theoretical justification and practical implementation of entropy extractors based on national cryptographic algorithms

2026-01-19T12:15:19+02:00

Improving the process of obtaining randomness requires special attention in modern cryptographic systems and primitives. This is because random data that does not meet the requirements can significantly weaken or compromise cryptographic applications. Therefore, it is necessary to calculate keys and parameters of cryptographic transformations based on the use of verified randomness, as well as to standardize and certify methods and means of generating random sequences and numbers.

Currently, there is a high demand not only for new sources of randomness, but also for methods and means that can obtain sequences with good randomness properties from samples from such sources. This task is accomplished by entropy extractors. The NIST Special Publication 800-90B defines the procedure for collecting and evaluating entropy from relevant noise sources, as well as the procedure for applying entropy extraction to the obtained data so that the result meets certain requirements for entropy per bit, uniformity, and unpredictability.

The most important step in building an entropy extractor is choosing the proper noise source, as it contains a non-deterministic process that provides entropy and is essentially the basis of security for the entropy source and for the RNG as a whole. If the non-deterministic activity of the NS produces something other than binary data, the sampling process includes a digitization process.

Other essential steps in building an extractor include evaluating the entropy at the output of the selected noise source and then applying trusted cryptographic primitives to obtain uniform data with the required amount of entropy based on the noise source outputs.

The paper analyzes existing recommendations for constructing entropy extractors based on cryptographic primitives, provides a theoretical justification for the possibility of using national algorithms as such extractors, and gives examples of practical implementation of extractors based on national cryptographic algorithms.

Further research plans include developing a block_cipher_df extraction algorithm based on the Kalyna block cipher algorithm mentioned in this study, verification of the compliance of extractor outputs based on national cryptographic algorithms with the entropy requirements, as well as the application of extractor output extension components based on national algorithms to obtain sequences of arbitrary length.

Evolution of block symmetric cipher architectures

2026-01-19T12:40:17+02:00

The article presents an analysis of the evolution and design principles of block symmetric ciphers (BSCs), which are a direct implementation of the fundamental ideas of Claude Shannon.

A detailed comparative analysis of two classical iterative architectures is carried out, namely, the Feistel Network (FN) and the Substitution-Permutation Network (SPN), which have become the basis for most modern standards (including DES and AES). The key differences in their reversibility, requirements for the round function and diffusion rate are considered. Additionally, alternative designs such as the Leigh-Massey (LM) Network and the Generalized Feistel (GFN) Network, ARX (Add-Rotate-XOR) ciphers are investigated, emphasizing their role in providing faster diffusion and flexibility.

Three main directions of modern adaptation of BSNs are highlighted:

Performance on powerful processors: dominance of ARX (Add-Rotate-XOR) designs that replace traditional S-blocks with operations efficient for 32/64-bit architectures (e.g., ChaCha20);

Post-quantum stability: it is substantiated that BSNs such as AES-256 remain resistant to Grover's attack by doubling the key length;

Minimalism and Lightweight Cryptography: changing priorities to energy efficiency and minimizing hardware costs for IoT devices. This has led to the development of ciphers with very small S-blocks (like PRESENT), which compensate for the weaker round function by significantly increasing the number of rounds.

Thus, the article demonstrates that the architecture of BSS is a dynamic field that successfully evolves, effectively adapting to both theoretical threats (quantum computing) and hard practical hardware limitations.

Systematization of zero-knowledge proof methods

2026-01-19T13:08:35+02:00

The article systematizes modern methods of zero-knowledge proof (ZKP). Classification features are considered: protocol interactivity, algebraic or stochastic basis, need for trusted setup, type of zero-knowledge, and proof model. Classical schemes (Fiat–Shamir, Schnorr, Blum), modern zk-SNARK and zk-STARK, as well as novel approaches – PLONK, Halo 2, Bulletproofs, lattice-based ZKPs, and machine learning proofs are described. A comparative analysis is conducted according to efficiency, proof size, generation and verification complexity. It is shown that SNARKs provide compactness but require a trusted setup, while STARKs are transparent and post-quantum secure but large. Open problems are highlighted: recursive proofs, standardization, metadata protection, and applications in machine learning. It is concluded that further research in this field is aimed at creating scalable, secure, and quantum-resistant protocols for digital technologies.

Quantitative model of passive speech information concealment means using the nonlinear attenuators

2026-01-19T13:17:50+02:00

223. P. 44 – 50.

The application of nonlinear filters for protection against information reconnaissance is considered on the example of using the phenomenon of acousto-electrical conversion in auxiliary technical means at the object of information activity. The principle of operation of nonlinear filters, their characteristics, typical schemes of their application in the conditions of conducting intelligence of dangerous signals from outside the controlled territory are analyzed, with the development of a quantitative model.

It is shown that the reconnaissance operator is able to reduce the effectiveness of leakage protection by disconnecting the communication line from the telephone exchange. According to the results of the analysis, it is proposed to counteract this by shunting the communication line with a resistor within the controlled area. A quantitative model in the Python programming language allowed us to visualize the conclusions obtained.

Creating information security systems based on open portable trusted execution environment (OP-TEE), KVM/QEMU and intel trust domain extensions

2026-01-19T13:58:44+02:00

The purpose of the article is to study one of the approaches of OP-TEE framework integration with Intel-X86 platforms using intel trust domain extensions technology. The subject of research is the integration of OP-TEE framework with Intel-X86 VT-d/VT-x using Intel TDX, KVM and QEMU.

The solution proposed in the article is based on the isolation of the secure world into a separate TD. The solution is based only on Linux or Android used as the host OS, so Kernel-based Virtual Machine (KVM) is used as the virtualization system.

For the standard open-source implementation of OP-TEE, there is a QEMU implementation for ARM TrustZone platforms that integrate easily and run in a KVM environment. So, we can run OP-TEE/QEMU/KVM as TD.

The article will be useful to specialists in the field of information security, dealing with data protection in the operating systems of computer systems.

Overview of approaches to building secure, interference-resistant streaming video transmission systems for UAVs

2026-01-19T14:11:22+02:00

The article provides a systematic review of modern approaches that can be used to build a secure, interference-resistant system for transmitting streaming video from unmanned aerial vehicles (UAVs), in particular FPV kamikaze drones, which have become widespread in the military sphere. The problem of simultaneously ensuring cryptographic protection and interference resistance of the communication channel under the active influence of electronic warfare means is analyzed. Known solutions are considered, taking into account the requirements for such systems and the limitations imposed on them – ensuring minimal delay, limitations on computing resources and the sufficiency of ensuring temporary cryptoresistance, as well as the ability to function in interference conditions. The results of the study indicate the absence of an existing universal solution that would satisfy all requirements. The conclusion is made about the need to create new combined approaches to video stream encryption taking into account temporary stability, adaptability to channel conditions and the possibility of hardware implementation on FPGAs or systems on a chip.

Evaluation of the effectiveness of AI-based attacks on fingerprint biometric authentication systems

2026-01-19T14:26:49+02:00

The paper considers the urgent problem of information security in the context of the rapid development of artificial intelligence technologies and their use to bypass fingerprint biometric authentication systems. Сomparative analysis of modern attack methods was conducted, particularly synthetic generation technologies such as SpoofGAN and FingerFaker, as well as algorithms for reconstructing fingerprints from minutiae templates, such as the methods of Feng and Jain and also Buzaglo and Keller. The vulnerability of fingerprint authentication systems to cyber threats utilizing Generative Adversarial Networks was analyzed. It is noted that the greatest threat to personalized security is posed by reconstruction methods, which allow attackers to recover the unique papillary pattern of a specific individual from a compromised template.

Reconstruction attack method based on the Buzaglo and Keller approach was implemented. The architecture of the implemented method was described, which includes an algorithm for minutiae map formation, a ResNet50-based encoder for creating a latent vector, and a StyleGAN2 generator. Hardware and software requirements for deploying such an attack using CUDA and Python was described. The process of converting a discrete set of minutiae into a structured spatial representation and the subsequent generation of a realistic fingerprint image was described. A study was conducted using the standardized BOZORTH3 comparison algorithm to quantitatively assess the effectiveness of the proposed attack. Experimental results demonstrated the vulnerability of biometric systems to reconstruction-based attacks. It was established that even with strict security system settings with a False Acceptance Rate of 0.01%, the reconstructed fingerprints achieved a recognition accuracy of 96.68%.

A comparative analysis of the effectiveness of the implemented method against other AI-based attacks was performed. It was determined that while synthetic generation methods demonstrate high overall accuracy, the reconstruction method is critically dangerous specifically for targeted attacks on specific accounts.

Using deep learning methods for visualization and detection of malware

2026-01-19T14:46:12+02:00

The purpose of the article is to conduct a comparative analysis of the effectiveness of common convolutional neural network architectures for the task of classifying malware, which was previously converted into graphic images. The approach is based on converting executable PE-files into grayscale images. The transfer learning method is applied to classify these images. The paper provides an experimental comparison of seven architectures (XceptionNet, DenseNet169, EfficientNetB0, MobileNetV2, InceptionV3, ResNet50V2, and VGG16) based on Accuracy, Precision, Recall, and F1-score metrics to determine the most effective and computationally balanced model for threat analysis.

The article will be useful to specialists in the field of cybersecurity and machine learning who are involved in the development of intelligent systems for detecting "zero-day" and polymorphic threats.

Analysis of resistance of the FULEECA, WAVE, BISCUIT, and RYDE post-quantum digital signature algorithms

2026-01-19T15:00:57+02:00

Post-quantum digital signature algorithms are being developed as an alternative to classical schemes, capable of ensuring cryptographic security even in the presence of quantum computing power.

The results of the analysis and research of the FULEECA, WAVE, BISCUIT, and RYDE post-quantum digital signature algorithms, which are based on different cryptographic approaches to ensuring resistance in quantum computing environments — from code and rank schemes to multilateral quadratic constructions — providing multi-level resistance to a wide range of attacks, are presented.

The analysis showed that all the algorithms considered have high potential for use in post-quantum systems, meeting key requirements for security, performance, and efficiency. At the same time, each algorithm has its own requirements for resources, key and signature sizes, implementation features, and cryptographic resistance to classical and quantum attacks.

The results provide a basis for further comparative analysis, as well as for formulating recommendations for the application of each of the algorithms depending on the specifics of the information system, the level of threats, and the limitations of the implementation environment.

ML-WAF information technology for classification and blocking of injection attacks in a containerized Web environment

2026-01-19T15:12:07+02:00

This paper presents an adaptive ML-based Web Application Firewall (ML-WAF) designed for the classification and blocking of injection attacks in containerized web environments. The relevance of this work is driven by the widespread adoption of micro-services, container orchestration, and Kubernetes, which significantly reshapes the requirements for securing HTTP(S) traffic. Traditional signature-based WAF solutions exhibit limited effectiveness against SQL Injection, Cross-Site Scripting, and Command Injection due to their variability, contextual dependence, and susceptibility to evasion techniques. The aim of the study is to develop and experimentally evaluate a ML-oriented web-filtering technology that provides high-accuracy detection of malicious HTTP(S) requests, low processing latency, and continuous model self-updating within an MLOps pipeline. To achieve this goal, the paper introduces conceptual, structural, functional, and information-logical models of the ML-WAF, along with UML representations (Use Case, Activity, Class, Sequence) that formalize the architecture, behaviour, and interactions between system components. The proposed technology incorporates a multi-stage processing pipeline, including TF/IDF vectorization with enriched features, a KNN classifier, a risk-based decision engine (ALLOW/SANDBOX/BLOCK), monitoring and logging subsystems, and automated model retraining. A hybrid method of integrating the ML component into a WAF in Kubernetes is proposed, combining an Ingress Controller, a dedicated ML-service, and a Horizontal Pod Autoscaler. This approach ensures high scalability and stable performance under varying workloads. The practical evaluation was conducted in a Kubernetes-based containerized environment using realistic SQLi and XSS datasets and load testing with Apache JMeter. Experimental results demonstrate that the ML-WAF achieves a Precision of 0.95, Recall of 0.93, and an F₁-score of 0.94, with an average processing latency of 3.9 ms and a throughput of approximately 700 requests per second. The system reduced false positives to 2.3%, compared to 6.8% for ModSecurity, while scaling the ML-WAF to six Pods increased throughput by 27% without degrading classification quality. The presented results confirm that the proposed ML-WAF technology forms a robust foundation for next-generation AI-driven security gateways in cloud-native and containerized infrastructures.

Ethical principles and normative regulation of professional activity in cybersecurity: international standards, Ukrainian context, and practical guidelines

2026-01-19T16:33:47+02:00

This paper explores the ethical foundations and legal regulation of professional activity in cybersecurity amid digital transformation. The authors emphasize the growing importance of digital trust and moral responsibility in the daily work of cybersecurity professionals. A comparative analysis of European, American, and Ukrainian frameworks (including GDPR, ACM and (ISC)² Codes of Ethics, ENISA recommendations, and Ukrainian legislation) identifies key normative anchors and ethical principles. The study highlights complex dilemmas such as the boundary between privacy and surveillance, ethical vulnerability disclosure, and the role of cybersecurity experts during cyber conflicts. Attention is given to the need for professional certification standards to include ethical components, as well as the integration of ethics into organizational policies, audit procedures, and education. The paper proposes practical guidelines for ethical auditing, internal policy-making, and protection of responsible researchers. Recommendations are also made for harmonizing Ukrainian regulations with international ethical standards and for developing a national code of ethics. This research contributes to the development of a professional cybersecurity culture based on responsibility, transparency, and digital rights. The results are applicable in academic curricula, policy design, and industry governance.

Unified cryptographic coprocessor architecture for post-quantum cryptography in 6G network equipment

2026-01-19T16:43:18+02:00

The advent of quantum computing poses significant threats to current cryptographic infrastructure protecting 5G and emerging 6G networks. In August 2024, the National Institute of Standards and Technology (NIST) published the first post-quantum cryptography (PQC) standards: ML-KEM (FIPS 203) for key encapsulation and ML-DSA (FIPS 204) for digital signatures. Real-world security protocols such as TLS 1.3 and IPsec require both operations simultaneously, necessitating efficient unified hardware implementations. This paper presents a novel unified cryptographic coprocessor architecture (UniPQC) supporting both ML-KEM and ML-DSA algorithms for deployment in 6G network equipment. The proposed architecture leverages the shared mathematical foundation of both algorithms, specifically the Number Theoretic Transform (NTT), to achieve significant resource optimization. We implement a configurable NTT engine with shared butterfly units capable of processing both 256-coefficient polynomials for ML-KEM and ML-DSA with different moduli (q=3329 and q=8380417). The architecture includes: Unified Polynomial Arithmetic Module (UniPAM), Hash and Sampling Unit (HSU) with Keccak-f[1600] core, Memory Management Unit (MMU) with conflict-free addressing, and Control Configuration Logic (CCL). The architecture is implemented on Xilinx Zynq UltraScale+ FPGA, achieving 285 MHz operating frequency with 4,512 LUTs, 3,245 FFs, 24 DSPs, and 8 BRAMs. Performance evaluation demonstrates that the unified design reduces area-time product by 34% compared to separate implementations while meeting the latency requirements for 6G Ultra-Reliable Low-Latency Communication (URLLC) applications. Complete TLS 1.3 handshake is achieved in under 300 μs, with power consumption of 245 mW for ML-KEM and 312 mW for ML-DSA operations.

Hierarchical clustering using a Kohonen neural network for secured wireless sensor networks

2026-01-19T16:53:13+02:00

In today's world, wireless sensor networks (WSNs) have found widespread application in environmental monitoring systems, smart cities, healthcare, and military technologies. However, despite their flexibility and scalability, WSNs remain vulnerable to a wide range of cyber threats, namely, from data interception to routing attacks and node spoofing. This study explores an approach to information protection in WSNs based on node clustering using the Kohonen neural network.

Modeling of clustering in wireless sensor networks using the Kohonen neural network has demonstrated significant effectiveness in solving the problem of adaptive network structure management. The generated topological maps show the network’s ability to self-organize, form stable clusters, and integrate new sensors without disrupting classification logic. The Kohonen network successfully distributes sensors based on behavioral features, creating stable and adaptive clusters. The introduction of a new sensor and its automatic assignment to a cluster confirms the model capacity for dynamic response. Cluster formation hat considers residual energy and spatial centralization contributes to energy conservation and extends the network lifecycle.

The proposed clustering approach based on the Kohonen neural network enables an efficient, flexible, and adaptive WSN structure, especially under dynamic operating conditions. Automatic determination of cluster membership for new sensors facilitates rapid response to topology changes without the need for centralized processing. The self-organizing nature of the Kohonen network makes it a promising tool for early detection of cyber threats through node behavior classification. Simulation results demonstrate the advantages of neural approaches in tasks related to information protection, network adaptation, and energy consumption optimization.

Detection of new radio emissions in automated radio monitoring

2026-01-19T17:45:40+02:00

The purpose of this work is to develop and investigate methods for detecting new radio emissions against a background of stationary interference under conditions of a priori uncertainty.

The methods used include the approach based on a probabilistic model of orthogonal expansions of observations. Decision rules were developed by comparing the Mahalanobis distance and Euclidean distances between current and reference signal energy spectra. Experimental studies were conducted on samples of real data from the shortwave range.

The main results and significance proposed and justified here include a family of detection algorithms, adapted to conditions of a priori uncertainty (particularly for Gaussian distributions). Experimental results confirmed the high effectiveness of the proposed algorithms. The developed algorithms are suitable for application in automated radio monitoring systems for the timely detection of new radiation sources.

Critical analysis of known missile guidance methods

2026-01-19T17:57:38+02:00

Modern missile guidance methods play a key role in ensuring the effectiveness and reliability of air and missile defense systems. The choice of an appropriate guidance method directly affects target interception accuracy, flight time, and hardware implementation requirements of control systems. Until recently, most guidance methods were developed for limited engagement conditions, making their critical analysis particularly relevant from the standpoint of modern requirements.

The purpose of this study is to analyze and systematize well-known missile guidance methods to identify their advantages, limitations, and areas of effective application. Studying this issue makes it possible to obtain a deeper understanding of the current state of missile guidance theory and to substantiate the necessity of further research in this field. Thus, the article aims to perform a comparative analysis of classical guidance methods and to formulate requirements for a prospective guidance method capable of improving the performance of air and missile defense systems.

The paper considers pursuit guidance, constant lead angle guidance, proportional navigation, and parallel navigation methods. Their kinematic trajectories, application conditions, and compliance with the main requirements for modern guidance algorithms are analyzed. It is shown that none of the considered methods simultaneously satisfies all the stated requirements. Based on the performed analysis, the relevance of developing a new guidance method is substantiated. This method should be based on the further development of parallel navigation and incorporate an agent-oriented approach in three-dimensional space.

Evaluation of the effectiveness of distance determination using the ARCore framework in low-light conditions

2026-01-19T18:07:00+02:00

This paper presents results of the experimental evaluation of distance measurement accuracy using the ARCore under low-light conditions. The study employed a POCO X5 Pro smartphone with a test application, an Ekotenzor-03 photometer, and an INKERSI KE50 laser rangefinder as a reference. It was found that at illumination levels below 30–40 lx, errors increase significantly, especially at distances over 2 m, leading to failures in depth map generation. Applying averaging and median filtering across multiple measurements partially improved stability but did not eliminate the dependence on illumination. The results complement previous studies conducted under daylight conditions and outline practical limitations of the ARCore for navigation systems for visually impaired users.

Simulation of a slice phantom of human vertebra trabecular tissue for the study of its CT reconstruction

2026-01-19T18:24:59+02:00

The relevance of the study is due to the need to assess the influence of CT reconstruction settings on the accuracy of calculating the parameters of the trabecular bone of the vertebrae. The aim of this study is to develop a digital phantom that accurately reflects the microarchitecture of trabecular bone tissue and can be used to model the results in real scanning conditions, with subsequent comparative analysis of morphometric parameters of cancellous bone obtained using CT. The phantom model of the trabecular bone section was developed based on histological characteristics obtained from micro-CT images. The complete workflow for the synthesis of a digital phantom of bone structures is based on micro-CT with subsequent complex data processing, including sinogram generation and image reconstruction. The projection sinogram was generated using the Radon transform with a predefined angular step, and then subjected to CT image reconstruction. The procedure for constructing and studying a digital CT phantom consisted of several key steps: phantom generation, simulation of its CT image under conditions close to those of real clinical scans, and subsequent quantitative assessment of discrepancies between phantom image parameters and the reconstructed image. The results demonstrate the possibility of modeling trabecular bone architecture using a digital phantom, which provides a reproducible basis for quantitative assessment of bone microstructure. All stages of calculations and modeling were performed in the MATLAB environment (R2023b, MathWorks version) using the Image Processing Toolbox for image processing, as well as specially developed scripts for morphometric analysis adapted to the specific characteristics of trabecular architecture.

Optimization of fluctuating power of diesel generators used in avionics systems

2026-01-19T18:33:14+02:00

The article is devoted to the consideration of methods for optimizing the fluctuation power of low-frequency frequency generators. The power supply to the forming mechanism is determined by the amplitude of the frequency-modulated components of fluctuation noise, their analytical analysis was carried out and the results of experimental observations were compiled. A clear geometric interpretation of the mechanism for minimizing the fluctuation parameters of the diode generator is given.

Among the significant number of methods for tracking the fluctuation parameters of diode generators in the robot, the vicor is the method of separating their noise into amplitude-modulated and frequency-modulated components. Based on a thorough analysis of other optimization methods, the optimal operating modes of the generator on avalanche flow diodes were determined from the point of view of its fluctuation authorities.

The results of the investigations make it possible to optimize or regulate the level of their noise fluctuations during the design process of low-frequency generators.

Spectral Simulation of Mode Competition in a Magnetron with an Essential Influence of Space Charge

2026-01-19T18:49:03+02:00

The article investigates the excitation and competition of different types of oscillations (modes) in a resonant system of a typical 2450 MHz magnetron of medium power (1 kW), which are usually used in microwave ovens for household and corporate purposes. A feature of such magnetrons is the significant influence of space charge forces on the process of spoke formation during the mutual transformation of modes while the “hopping” of modes. Inevitably, in such cases, the expansion of the spectrum of the output signal can, under several conditions (primarily, inadequate quality of the high-frequency shielding system), significantly worsen the electromagnetic environment around the microwave device, which can lead to disruption of the operation of Wi-Fi communication systems in adjacent frequency ranges.

The research is carried out by the method “Particle in Cell” using the Magnol Problem of the TULIPgm application package. A two-dimensional approximation and a second-level spectral model (the method of complex amplitudes) are used. The spectra of the output signal and the induced current of the probe, which is in the middle of the interaction space, are analyzed. During the research, it was possible to simulate the transition process between the working (N/2) mode of oscillations and the high-voltage neighboring (N/2–1) mode. Further transition to the (N/2–2) mode does not occur, instead the destruction of the spoke grouping takes place. During the transition process, a significant (although relatively short-term) broadening of the spectra is observed. The spectrum of the output signal when operating on the N/2–1 mode is analyzed in detail, in particular, the preservation of the component with the frequency of the operating (N/2) mode of relatively large amplitude is established. The essential effect of the space charge in relatively low-power magnetrons leads to significant nonlinearity of the electron cloud, which sharply increases the amplitudes of the intermodulation components during the transition processes and creates the phenomenon of anode voltage hysteresis when switching from one mode of oscillation to another and vice versa. Based on the research performed, design solutions can be proposed for further optimization of the operating modes of the most common magnetron generators.

Composition, structure and microhardness of multicomponent tungsten carbide based coatings formed using the inverse magnetron sputtering system

2026-01-19T19:06:34+02:00

The subject of research is the processes of forming multicomponent coatings based on tungsten car-bide (WC) by sputtering of elements by the ion-plasma method. The aim is to study the influence of metals from the composition of its structural parts on the structure and microhardness of WC coatings formed using an ion-plasma spray system. The task is to study the effect of metals from the composition of the structural parts of the magnetron sputtering system on the period of the crystal lattice, the size of the coherent scattering region X-rays and the microhardness of WC coatings. The methods used in the research: X-ray diffraction analysis, scanning electron microscopy and microhardness. The results obtained: coatings based on WC coatings with a thickness of 3-6 microns. The coatings also contain the following elements: Fe, Mo, Cr, Ni, Ti, and O. Content of W in the samples varies widely. Moreover, with a decrease of this element, the iron content increases. At the same time, the chromium content varies slightly from sample to sample. Nickel and titanium are found only in in some samples. It was found that the structure of the coatings belongs to the B1 type, the spatial group is №225. In all samples the lattice parameter of tungsten carbide lattice parameter of tungsten carbide significantly exceeds the value known from the literature (a = 4,215Å). An important feature of the studied coating samples is the presence of a (200) texture in most of them. With an increase in the area of coherent scattering of X-rays, a tendency towards a decrease in the crystal lattice period and microhardness of the coatings is observed. Conclusions. The scientific novelty of the obtained results lies in the fact that for the first time the influence of metals from the composition of the structural parts of the inverted magnetron sputtering system on the crystal lattice period, the size of the coherent X-ray scattering region, and the microhardness of WC coatings has been established. At the same time, for the entire set of samples coatings, these parameters correlate with each other. The data obtained indicate the prospects for controlling a wide range of physical and technical properties of multicomponent coatings based on tungsten carbide during their formation using inverse magnetron sputtering systems with sectioned cathode units.

BLDC motor control systems analysis

2026-01-19T19:30:27+02:00

Modern BLDC motor control methods play a key role in ensuring the efficiency and reliability of their operation. Until recently, controlling these motors was a complex task, requiring high costs for specialized equipment and software. However, thanks to the constant development of technology, today's control methods have become more accessible and effective. The purpose of this study is to review English-language scientific sources devoted to BLDC motor control methods. Studying this issue will allow to obtain a deeper understanding of current trends and achievements in this area, which plays an important role in the further development of electrical systems and devices. Thus, this article sets itself the task of systematizing and analysing the scientific literature on BLDC motor control in order to highlight the current state of research in this area and identify prospects for further development. This article discusses the main aspects control systems for brushless DC motors (BLDC), which play an important role in modern technologies. The relevance of the study lies in the need to develop effective and reliable control systems to ensure optimal performance and functionality of devices using BLDC motors.