REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE
The journal publishes original papers in English, French, German, and Russian, representing research on power economy, electrical power, electrical engineering, electronics, information transmission, computers, control systems in electrical power, thermopower, thermomechanics, bio-medical engineering, and related problems. It reflects especially the fundamental and experimental research activity in power and communications of our country, papers presented at international conferences held in Romania, as well as the contributions of some specialists from abroad. A special part is assigned to reviewing the most relevant books, appearing in Romania and from abroad. The papers published are of a high level of the modern sciences and technique and represent original contributions to the development of contemporary power sciences. All manuscripts are strictly refereed and only papers of high quality, original, and with the application of the results, are accepted for publication. Through its topics, Revue is of concern to specialists working in research and education, doctoral candidates, and senior-year students. Revue Roumaine des Sciences Techniques, Série Électrotechnique et Énergétique is a journal of the Romanian Academy, the Engineering Section
The Publishing House of the Romanian Academy
SPEED SENSORLESS SLIDING MODE CONTROL FOR DUAL STAR INDUCTION MOTOR BASED ON HYBRID PSO-GWO ALGORITHM
This paper presents a sliding-mode model-reference adaptive system (SM-MRAS) observer for speed estimation in a sensorless, indirect vector control dual-star induction motor (DSIM) system. Firstly, a reference model of the DSIM rotor fluxes is provided using a voltage-model observer. The adjustable model adjusts the rotor flux estimates to match the reference model by adapting the speed, especially the speed estimate, which is a sliding-mode term. Secondly, the optimal parameters of the sliding mode controllers are optimized by the hybrid particle swarm grey wolf optimization (PSOGWO) algorithm. The main objective of this study is to demonstrate the effectiveness and validity of the proposed SMC-PSOGWO strategy. A comparative analysis with SMC-GWO and the conventional PI controller illustrates that the proposed method achieves a faster dynamic response and superior overall performance.
Électrotechnique et électroénergétique | Electrical and Power Engineering
Particle swarm grey wolf optimization (PSO-GWO)
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EXPERIMENTAL CORRELATION OF THE CONVECTIVE HEAT TRANSFER COEFFICIENT FOR PV MODULE SURFACES
In this paper, a correlation for the convective heat transfer coefficient from the surfaces of photovoltaic (PV) modules is proposed. This correlation was established by experimentally measuring the temperature of PV modules under outdoor conditions, specifically using an open rack-mount setup in which the modules are placed on a freestanding frame and exposed to the surrounding environment. The coefficients of the assumed power-law correlation between the convective heat transfer coefficient and the magnitude of the local wind velocity are determined using the particle swarm optimization (PSO) algorithm and the least-squares method, and the results are compared with measured PV module temperatures calculated using a transient thermal model. Finally, the proposed correlation is compared with similar correlations of this type. While some correlations for the convective heat transfer coefficient yield an average difference of nearly 10 °C between the calculated and measured temperatures of the PV module, the proposed correlation allows the PV module's temperature to be estimated with a deviation of no more than 3 °C.
Thermotechnique et thermoénergétique | Thermotechnics and Thermal Energy
ARCHITECTURE FOR INTEGRATING AIR QUALITY DATA FROM MULTIPLE SOURCES
Air quality (AQ) monitoring has become an imperative component of public health strategy, yet traditional monitoring paradigms need improvement, and legacy systems designed for specific regional compliance struggle to keep up with the complexity of the problem. The study of existing air quality data reveals a variety of sources, data formats, and diverse parameter definitions across data providers. This paper proposes an architectural blueprint for a layered system capable of integrating air quality data, streamlining access to data from multiple sources into a single location, and reducing data heterogeneity to a common ground. The solution presented is implemented as an iOS software development kit (SDK) to demonstrate its practicality, with the long-term objective of transforming a disparate data landscape into a cohesive platform.
Automatique et ordinateurs | Automation and Computer Sciences
Software development kit (SDK) architecture
ANALYSIS OF THE TIME-FREQUENCY LOCKED LOOPS USING TABLES - PART 1
Time-frequency locked loops (Time-FLL) are linear discrete systems based on the processing of the input signal periods. This article describes one tabular approach to analyzing Time-FLL. This tabular method of analysis enables the complete escaping of a very long mathematical procedure. The approach is presented in the tracking and prediction applications of Time-FLLs, but it can also be used in its other applications, for instance, in digital filtering of the input periods, noise suppression, and others. This approach can also be applied to any linear discrete system. The paper first presents a mathematical procedure for analyzing systems of the lowest order. Based on these results, the table approach was discovered and extended up to Time-FLLs of the tenth order. The table can be simply extended to the Time-FLL of any order. Mathematical analysis and time-domain simulation were performed, along with frequency-domain analysis. To prove the correctness of the tabular approach, the properties of the third-order Time-FLL3 and the seventh-order Time-FLL7 are demonstrated in the time and frequency domains.
Électronique et transmission de l’information | Electronics & Information Technology
STUDIES ON THE DESIGN AND ANALYSIS OF SLOT-LOADED PATCH ANTENNA FOR X-BAND APPLICATIONS
In this article, a miniaturized square slot-loaded patch antenna with a rectangular bulged slot and a complementary π-shaped slot carved on the ground plane is proposed. The tri-band of resonant frequencies was obtained by exciting a rectangular bulged slot and a complementary π-shaped slot with a microstrip-fed slot-loaded patch antenna. FR-4 dielectric substrate of 50 mm x 50 mm x 1.56 mm has been used to fabricate the antenna. The resonant frequencies of 8.4, 9.4, and 11.9 GHz were acquired for X-band applications, including wireless networks, radar systems, and satellite communications. Impedance matching and wide bandwidth are achieved with the implementation of the defected ground structure (DGS) technique. The experimental validation of antenna characteristics, including reflection coefficient, gain, bandwidth, and radiation efficiency, demonstrates strong concordance with simulated results.
Génie biomédical | Biomedical Engineering
DUAL GEOCHEMICAL GAS MONITORING SENSOR USING ACTIVE TEMPERATURE DISTURBANCE REJECTION METHOD
An active temperature disturbance rejection method was developed to address uncertainties in temperature disturbances and to improve stability for field gas measurements. A symmetric convection heat conduction strategy was used to ensure uniform heating of the multipass cell (MPC). Active disturbance rejection control (ADRC) was adopted to address the nonlinear and uncertain temperature disturbance. The temperature fluctuation is less than 0.01℃ in the stable state during field experiments when controlled at 30℃. The maximum temperature fluctuation during gas sample replacement is less than 0.015 °C. For gas measurement results, CO2 and CH4 concentrations were monitored at 2100-3864 ppmv and 99-104 ppmv, respectively. This temperature control method provides a guarantee for field gas monitoring.
PARAMETER ESTIMATION OF COMPOUND-GAUSSIAN CLUTTER WITH NAKAGAMI-DISTRIBUTED TEXTURE
This paper addresses the parameter estimation of the compound-Gaussian clutter with Nakagami texture (CGNG). The CGNG distribution was recently introduced to model high-resolution sea clutter. Two estimators are proposed: the fractional-order moment estimator (FOME) and the fractional-negative-order moment estimator (FNOME). The estimation performance of the proposed estimators is assessed and compared with that of the existing higher-order moment methods (HOME) and the [zlog(z)] estimator. Using both simulated and real data, estimation accuracy and modeling performance are evaluated using the chi-squared test (χ2) and the mean square error (MSE).
Compound-Gaussian clutter with Nakagami (CGNG) distribution
LANE BOUNDARY DETECTION IN DYNAMIC ENVIRONMENTS
Lane detection is essential for collision warning systems. This technology helps vehicles maintain proper road position by identifying lane markings. This paper presents a method for lane detection within an ADAS using a monocular camera in real time. The approach uses the Hough Transform to detect lane lines in an image. The detected lines are filtered based on specific criteria, including angle, length, and symmetry relative to the image’s central axis, to select the best lines representing the lane boundaries. These techniques are crucial for improving the precision of driver assistance systems by ensuring reliable lane detection, even under varying conditions. Experiments were conducted in MATLAB using the publicly available TuSimple dataset, which contains diverse road scene images. The results indicate that the proposed method achieves precise lane-line detection, which is crucial for real-time monocular vision-based driver-assistance systems, thereby significantly enhancing road safety
Advanced driver assistance system (ADAS)
SOLVING COMBINED ECONOMIC AND EMISSION DISPATCH PROBLEM USING A ONE LAYER DYNAMIC NEURAL NETWORK
In this paper, a one-layer dynamic neural network (OL-DNN) has been proposed to find optimal solutions to combined economic and emission dispatch (CEED) problems. The goal of the CEED problem is to schedule generators to meet load demand and operational constraints while minimizing fuel costs and emissions. The fuel cost and emission objectives of the generating units are taken into account when formulating the CEED problem from a multi-objective to a bi-objective problem. This is done by applying a price penalty factor. The new algorithm is applied to and tested on three examples from the literature, and the solution is then compared with those obtained by other algorithms to demonstrate the superiority and effectiveness of the proposed algorithm.
RECREATION OF THE INDEX METACARPAL BONE USING 3D PRINTING FROM RADIOLOGICAL
Accidents often cause fractures, and since bone regeneration is difficult, the loss can be replaced with artificial bones. The article aims to replace the original bone model using radiographic-based replacement techniques. The radiographic image (2D) of that particular fractured bone is converted into the 3D structure. Since radiographic images are 2D, they are converted into 3D using image processing techniques. The process involved replacing the new bone structure by converting a 2D X-ray image into a 3D model using MATLAB and CATIA. In this process, the following image processing techniques are used: grayscale conversion and K-Means clustering-based Segmentation. Finally, the CATIA software is used to obtain the required 3D image of the metacarpal bone to be replaced. Finally, using a 3D printer, the metacarpal bone 3D structure was created from calcium hydroxyapatite, measuring 56.33 mm in length.
GRAPHENE PATCH ANTENNAS FOR SATELLITE RADAR: SUBSTRATE AND CHEMICAL POTENTIAL ANALYSIS
This paper presents the design, simulation, and experimental validation of high-performance rectangular patch antennas and their arrays specifically designed for X-band radar applications. CST Microwave Studio was used to enhance the antenna designs, maximizing radiation efficiency and achieving optimal performance at 10 GHz with the appropriate impedance. Rogers RT5880 outperformed FR-4 across gain, reflection coefficient, and voltage standing wave ratio (VSWR) when compared with two substrates. The work culminated in the development of a four-element antenna array, achieving a remarkable gain of 11.82 dBi. The experimental measurements prove the validity of the simulated results, confirming that this design is viable and can be used in advanced satellite communications. Graphene is also explored as a conducting material due to its tunable electrical properties by chemical potential variations, and its performance is compared with that of conventional copper. All these novel improvements contribute to the development of next-generation reconfigurable antennas that offer greater flexibility and performance for high-quality satellite radar communication.
Radar satellite communication Antenna arrays
REAL-TIME SOIL CONTAMINANT MONITORING USING MICROBIAL BIOSENSORS AND SUPPORT VECTOR MACHINE
Continuous‍‌ real-time monitoring of soil contamination is imperative for environmental safeguarding. Traditional laboratory-based analyses, however, are slow, expensive, and not viable for continuous on-site field work. In this work, we propose a hybrid soil monitoring strategy that combines microbial biosensors with a Support Vector Machine (SVM) classifier for quick detection of contaminants. Specifically modified Escherichia coli bacteria are engineered to react specifically to lead (Pb²⁺), mercury (Hg²⁺), and organophosphate compounds. They do this by generating electrical bio-signals with voltages ranging from 0.2 V to 1.5 V at contaminant concentrations above 50 ppm. The bio-signals are converted to digital form using a 12-bit ADC at a 1 kHz sampling rate, and then filtered, normalized, and statistical features extracted. A dataset containing 3,200 measurement points gathered over three months is used, of which 1,200 are used for both training and validation of the SVM. Using a radial basis function kernel, the system under discussion achieves 96.8% classification accuracy and 96.4% F1-score across the five soil condition categories. Sensor drift is compensated for through online model updating; thus, the system is reliable and capable of continuous soil contamination monitoring in a field environment.
THREE-END TRAVELING WAVE FAULT LOCATION BASED ON ELECTROMAGNETIC DECOUPLING
This study introduces a novel three-end traveling-wave-based fault location (TW-FL) method for transmission lines to improve fault location accuracy and speed. Unlike traditional approaches, it eliminates the need for traveling-wave velocity and line-parameter measurements by analyzing current surges at three terminals and exploiting the time-of-arrival (TOA) of fault-induced waves to compute the fault location. For validation, the velocity implicitly derived from the TOA formulation was compared with its theoretical value, achieving an estimation accuracy of up to 99.96%, confirming the internal consistency and robustness. The model attained maximum and minimum fault location errors of 0.36% and 0.0803%, respectively, over 100 km from terminal P, demonstrating superior accuracy relative to existing models. Simulations conducted in PSCAD/EMTDC under various fault conditions verified its robustness, while validation of the WSCC 9-bus system confirmed its speed and reliability in improving grid performance and reducing power outage.
PUSH-PULL CONVERTER FOR MILD-HYBRID AUTOMOTIVE APPLICATIONS
The push-pull converter is an optimal solution for low- and medium-power automotive applications, providing galvanic isolation and simple construction. This paper evaluates the efficiency of a converter designed in a push-pull configuration for the automotive domain, powered by a 24 V ± 6 V input and delivering a 48 V output. The proposed converter, used in advanced start-stop systems for mild-hybrid and full-hybrid vehicles, operates with variable switching frequencies between 70 kHz and 300 kHz and various power levels. The output voltage ripple is a critical parameter in the design and performance of DC-DC converters, as it directly influences the required output capacitance connected in parallel with the load. Existing analytical expressions for estimating the ripple, normalized to the average output voltage, have primarily been developed under the assumption of continuous conduction mode (CCM) operation. The proper functioning of the converter and the efficiency variation across different operating regimes were validated theoretically, through simulation, and experimentally. This paper proposes a new formula that uses real circuit parameters for determining the efficiency of the push-pull converter. The derived formula has been validated through both simulation and experimental results, demonstrating strong agreement between the theoretical and experimental outcomes. Although it provides accurate results under the analyzed conditions, the proposed formula can be further improved by including additional factors specific to real operating conditions.
ELECTROMAGNETIC INTERFERENCE AND POWER QUALITY BEHAVIOR OF SELECTED COMMERCIAL LED DRIVERS
Over the last decade, the domestic lighting market in Romania has been significantly transformed by the adoption of LED technology. Despite compliance with EU standards, LED product quality still varies, making it essential to evaluate their performance and impact on the power grid. This paper presents a detailed analysis of power quality (voltage and current harmonics) and electromagnetic interference in both common-mode and differential-mode, using time- and frequency-domain measurements of two commercially available LED drivers. The results indicate that, while LEDs offer substantial energy savings, some products generate notable harmonics and EMI, in certain cases exceeding recommended limits, highlighting the importance of careful product selection and characterization for reliable grid integration.
A PROTOTYPE OF DIRECT-DRIVEN ELBOW ORTHOSIS ACTELMO WITH HARD AND MYO ON/OFF CONTROL
Elbow joint disorders occur after stroke and other neurological disorders, daily or sports traumas, etc. Rehabilitation with technical devices is a promising approach for helping these people return to normal life. To present an active wearable direct-driven elbow orthosis, ActElMO, and to conduct experiments with healthy subjects. The 3D-printed orthosis, with its anatomical design, is directly driven by an electrical actuator. The onset of elbow flexion can be set manually, without user effort, or via an electromyographic (EMG) signal from the biceps brachii (BIC) muscle. Experiments with 10 healthy subjects at various flexion velocities used this on/off EMG control, with individual thresholds set. The EMG signals from the muscles BIC and triceps brachii, and the elbow angle were recorded and processed. Different ways of EMG signal processing were tested. The chosen electrical motor provides sufficient power for rapid forearm movement with the orthosis. The device, including its trunk attachment, is user-friendly and convenient. The EMG signal from the BIC muscle is suitable for on/off control.
CHARACTERIZATION OF MULTILAYER SUPERHYDROPHOBIC SURFACE FOR ENHANCED HIGH VOLTAGE INSULATION
Superhydrophobic surfaces are widely used in electrical systems to repel moisture and enhance insulation performance. However, their exposure to environmental contaminants can degrade them over time. This study aims to characterize the properties of additional layers by analyzing their optical and structural characteristics. To evaluate the impact of multilayer deposition on their performance, several samples were prepared, then analyzed by FTIR, SEM, spectrometry, and contact angle measurement. The results indicate that increasing the number of layers enhances the structural uniformity, electrical stability, and optical transmission. These findings show the importance of multilayer structures in optimizing these surfaces, especially for electrical insulation.
COMPARISON OF FRACTIONAL ORDER PID AND PID CONTROLLERS: A NOVEL TUNING METHOD AND PERFORMANCE ANALYSIS
This study presents a direct comparison between fractional-order PID (FOPID) and classical PID controllers using a novel regularization-based tuning technique originally developed for integral-order controllers and adapted for fractional-order applications. Although the optimization problem is not convex by its nature, the objective function sweep results indicate the weak convexity of the problem, which validates the proposed method. Simulation results illustrate that the integral order (λ) is typically close to 1, which suggests that there is little advantage in integrating the fractional order in the conventional case. But improvements were noted in systems with positive zeros (far from the origin), long dead times, and high order. In these cases, FOPID carriers reduced ITAE by 20–30%, reduced settling time by 10–30%, and increased phase margin by up to 30%, further demonstrating better performance and robustness. The advantages stem from the softer polynomial kernel of the fractional derivative, which provides more flexible control in systems with intricate or suspended dynamics than classical PID controllers.
SPECIFICS OF SPECTRAL-CURRENT DIAGNOSTICS OF DEFECTS IN INDUCTION MOTOR BEARINGS
The paper theoretically substantiates the influence of defects in motor bearings on the form of their stator current and demonstrates the potential use of amplitude-defined spectral components of stator current as diagnostic indicators for bearing defects. It is shown that during bearing wear, rotor slot harmonics due to eccentricity directly interact with changes in magnetic conductivity across non-uniform air gaps, resulting in significant increases in harmonic amplitudes at rotor speed frequencies. Experimental investigations were conducted to validate these theoretical findings, confirming them comprehensively.
INDUCTION MOTOR BEARING FAULTS DIAGNOSIS USING AN IMPROVED KURTOGRAM METHOD
It is well known that the bearing’s outer race is the most failing part of the rolling-element bearings used in induction motors, which causes, in most cases, the complete shutdown of the entire industrial process. Moreover, the early diagnosis of this fault is essential to improve the operational reliability of these motors and in order to avoid huge financial losses. In this aim, demodulating the stator current envelope is a promising diagnostic approach, allowing direct extraction of the fault signature without being affected by the fundamental frequency. In addition, the Kurtogram, a statistical tool of 4th order spectral analysis, makes it possible to extract the signature of the searched faults even in the case of non-stationary signals. Therefore, the purpose of this paper is to address a comparative study between two Kurtogram-based computation algorithms: Fast-Kurtogram and Wavelet-Kurtogram. The experimental results obtained by the stator current spectral analysis show the superiority of the Wavelet-Kurtogram compared to the Fast-Kurtogram in the detection and localization of the outer race fault.
DSPACE REAL-TIME IMPLEMENTATION FOR CONTROL OF WIND-POWERED WATER PUMPING SYSTEM USING PERMANENT MAGNET SYNCHRONOUS GENERATOR
This paper investigates the control of a wind-powered water-pumping system using a permanent-magnet synchronous generator (PMSG) driven by a wind-turbine emulator. The system consists of an induction motor powered by the PMSG through a back-to-back converter, with AC/DC and DC/AC conversion stages. The first section of this paper discusses the modeling and control of the wind-water pumping system, particularly in rural and remote regions. The performances of the turbine, the PMSG, and the IM Centrifugal pump are analyzed. Simulation results have demonstrated good performance and verified the validity of the proposed pumping system under different operating conditions, including wind speed, rotor reference speed, and torque pump variation. To validate the proposed control method, simulations were conducted in MATLAB/Simulink. In the second part, experimental validation was conducted using the dSPACE 1104 control board, enabling real-time data acquisition and control.
SUSTAINABLE WIND RESOURCE ASSESSMENT USING ADAPTIVE WEIBULL ESTIMATION TECHNIQUES IN DATA-SCARCE REGIMES
Accurate wind data is important for clean energy planning. However, many weather datasets have missing values due to sensor issues. This study explores how missing data affects Weibull parameter estimation and compares four methods: the empirical method of Justus (EMJ), maximum likelihood estimation (MLE), moment method (MM), and least squares method (LSM). Five years of data (2020–2024) from 14 stations in Southern Thailand were used. Wind speeds ranged from 0.35 to 2.18 m/s, with a peak of 32.98 m/s. Data completeness varied from 27.61% to 84.14%. Model accuracy was tested using MAPE, RMSE, Chi-square, and R². EMJ and MM gave strong results with complete data. MLE worked best with 50–80% completeness. LSM showed high R² but overfitted with missing data. MM was the most reliable overall. These findings support better wind modeling in areas with limited data, helping clean energy development in Southern Thailand.
USING DC DECAY TESTS FOR DETERMINING THE MAGNETIZATION PARAMETERS OF THE AC ELECTRICAL MACHINES
The paper presents the use of a static experimental method (DC decay test) for determining the magnetization parameters of AC electrical machines. The magnetization characteristics, synchronous and differential magnetization inductances as functions of the total magnetizing current, were determined for two types of synchronous machines and an induction machine, respectively. The orthogonal d-q mathematical model in rotor coordinates was used, and the calculations were performed using MATLAB-Simulink. For the experimental tests, high-performance professional measuring devices were used.
GEOMETRY-DRIVEN MAGNETIC FIELD DECAY IN RECTANGULAR PERMANENT MAGNETS
The behavior of magnetic fields generated by permanent magnets is central to magnetic targeting applications, yet the influence of magnet geometry remains insufficiently characterized experimentally under controlled conditions. In this study, a systematic experimental framework was developed to isolate the effects of thickness and length in rectangular NdFeB magnets using a controlled 2×2 design and central-axis measurements. Field behavior was analyzed using complementary descriptors of local amplification, early axial decay, and spatial persistence, quantified by Ah (z), Dr, and zα, respectively. The results show that thickness primarily enhances near-field intensity, while length governs both spatial field persistence and early decay behavior. These effects are experimentally distinguishable, reflecting distinct geometry-dependent mechanisms. The study establishes a simple, experimentally validated framework for separating geometry-dependent contributions to magnetic field behavior, enabling consistent, physically interpretable comparisons of local amplification, early decay, and spatial persistence in targeting applications.
NONLINEAR DYNAMIC ANALYSIS OF TRANSFORMER SATURATION INDUCED BY SUBSYNCHRONOUS RESONANCE
This paper presents a novel investigation into the influence of post-fault subsynchronous resonance (SSR) on transformer flux dynamics and saturation behavior. A theoretical framework is established to examine resonance conditions in fixed-series-compensated transmission lines using frequency-domain impedance analysis, identifying electrical resonance points that can induce subsynchronous excitation. A nonlinear flux-voltage integral model is developed and implemented in MATLAB/Simulink to simulate transformer response under fault-clearing scenarios. Results reveal that the SSR-induced voltage recovery—particularly at 10 Hz—can drive the core flux well beyond the saturation knee, reaching up to 1.89 pu. The corresponding magnetizing current exhibits 20 Hz modulation, generating intermodulation sidebands at 40 Hz, 80 Hz, 110 Hz, and 130 Hz. Comparative analysis shows that series compensation significantly amplifies flux excursions and spectral distortion, confirming the role of transformer saturation as a nonlinear resonance amplifier. These findings underscore the importance of incorporating nonlinear transformer modeling into SSR studies for accurate assessment and mitigation in modern compensated power systems.
FAULT DIAGNOSIS IN POWER TRANSFORMERS USING RESAMPLED DISSOLVED GAS ANALYSIS AND MACHINE LEARNING
Fault diagnosis in power transformers is essential for ensuring operational reliability and minimizing maintenance downtime. This paper presents a hybrid machine learning framework that leverages advanced resampling and optimization techniques to enhance fault classification accuracy using dissolved gas analysis (DGA). To address class imbalance in the dataset, resampling methods such as SMOTE-ENN and ADASYN are employed. Three classifiers, namely nonlinear support vector machine (NLSVM), linear discriminant analysis (LDA), and artificial neural networks (ANN) are evaluated, with hyperparameter tuning performed using gradient-based optimizer function (GFO) and firefly optimization (FFO). Among them, the FFO-optimized NLSVM combined with SMOTE-ENN achieved the highest performance, with a recognition rate of 98.7%. The results, validated through confusion matrices and ROC analysis, demonstrate the robustness of the proposed approach. This framework provides an effective and reliable tool for condition-based maintenance, enabling precise multi-class fault identification in power transformers.
CONTACT RESISTANCE OF COPPER CONTACT WITH ZrCu THIN LAYER DURING ACCELERATED AGING
Reliability of electrical connectors is increasingly critical in modern automotive systems, particularly as the industry transitions toward fully electric vehicles with dense sensor networks and expanded data processing needs. Failures in connector interfaces can lead to severe system malfunction, equipment damage, or safety hazards. Among the various environmental and mechanical stressors that affect connector performance, electrical contact degradation, often evidenced by increased contact resistance, remains a primary concern. This study investigates the mechanisms and progression of contact degradation through controlled thermal aging of fabricated samples. ZrCu alloy coatings were deposited onto copper-clad laminates using cathodic arc technology to create representative contact interfaces. The evolution of contact resistance was monitored under low-current, low-voltage conditions to capture early-stage degradation effects. Results show a clear increase in resistance with aging, confirming the sensitivity of contact performance to factors such as oxidation, temperature exposure, and surface contamination. Additionally, the applied contact load was found to influence the effective contact area, thereby affecting overall resistance behavior.
A MODIFIED GAUSSIAN FUNCTION FOR MODELING MAGNETIC HYSTERESIS UNDER DYNAMIC CONDITIONS
This paper presents a novel modified Gaussian distribution for the Preisach model to improve magnetic hysteresis modeling. Unlike classical distributions, the proposed approach incorporates additional parameters that provide a more accurate representation of the dispersion of elementary relay switching thresholds. The influence of each parameter on the hysteresis loop shape is analyzed in detail. The model parameters are identified using the particle swarm optimization (PSO) method, based on experimental data. The simulation results are then compared with experimental measurements on a NiFe₂O₄ ferrite, accounting for dynamic effects due to temperature and frequency. The results show that the proposed model provides good agreement between simulation and experiment, particularly regarding the width and slope of the hysteresis loops.