SERBIAN JOURNAL OF ELECTRICAL ENGINEERING
Vol. 18, No. 3, October 2021

CONTENTS


Evgeniia Bulycheva, Sergey Yanchenko
Experimental Assessment of Harmonic Contributions Using a Ternary Pulse Sequence
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DOI: https://doi.org/10.2298/SJEE2103271B
Abstract: Harmonic contributions of utility and customer may feature significant variations due to network switchings and changing operational modes. In order to correctly define the impacts on the grid voltage distortion the frequency dependent impedance characteristic of the studied network should be accurately measured in the real-time mode. stis condition can be fulfilled by designing a stimuli generator measuring the grid impedance as a response to injected interference and producing time-frequency plots of harmonic contributions during considered time interval. In this paper a prototype of a stimuli generator based on programmable voltage source inverter is developed and tested. The use of ternary pulse sequence allows fast wide-band impedance measurements that meet the requirements of real-time assessment of harmonic contributions. The accuracy of respective analysis involving impedance determination and calculation of harmonic contributions is validated experimentally using reference characteristics of laboratory test set-up with varying grid impedance.
Keywords: Harmonic identification, Harmonic contribution, Impedance measure¬ment, Non-linear load, Power quality, Ternary pulse sequence.

George Karraz
Effect of Adaptive Line Enhancement Filters on Noise Cancellation in ECG Signals
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DOI: https://doi.org/10.2298/SJEE2103291K
Abstract: Power line interference is the main noise source that contaminates Electrocardiogram (ECG) signals and measurements. In recent years, adaptive filters with different approaches have been investigated to eliminate power line interference in ECG waveforms. Adaptive line enhancement filter is a special type of adaptive filter that, unlike other adaptive filters, does not require a reference signal and has potential application in ECG signal filtering. In this paper, a self-learning filter based on an adaptive line enhancement (ALE) filter is proposed to remove power line interference in ECG signals. We simulate the adaptive filter in MATLAB with a noisy ECG signal and analyze the performance of algorithms in terms of signal-to-noise ratio (SNR) improvement. The proposed algorithm is validated with Physikalisch-Technische Bundesanstalt (PTB) ECG signals database. Additive white gaussian noise is added to the raw ECG signal. Influential parameters on the ALE filter performance such as filter delay, the convergence factor, and the filter length are analyzed and discussed.
Keywords: Adaptive filter, Adaptive Line Enhancement, ECG, Power Line Interference.

Jeyapradha Ravichandran Banumathy, Rajini Veeraraghavalu
Optimal Design of Minimal Footprint High Frequency Transformer
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DOI: https://doi.org/10.2298/SJEE2103303B
Abstract: Transformer design procedure may vary essentially in respect of the transformer type and its operating frequency (ranging between 50/60 Hz and a few megahertz). This paper presents a simple and straightforward method based on the optimal choice of core geometry of a high frequency transformer (HFT) used in Solid State Transformer (SST) applications. The core of SST is the HFT which largely influences its size and overall performance. The proposed design procedure for HFT focuses on optimizing the core geometry coefficient (in cm5) with a constraint inflicted on loss density. The core geometry coefficient has direct impact on the regulation and copper loss and the procedure results in a robust overall design with minimal footprint. Also, the procedure intends to bring all the operating parameters like regulation, losses and temperature rise within permissible limits while retaining desired efficiency. Thus an energy-efficient design is achieved with minimal footprint. The optimization procedure is implemented using recently developed Moth-flame Optimization (MFO) algorithm. The results of the MFO algorithm are compared with the well-established PSO technique. An experimental prototype is built to validate the findings.
Keywords: Optimization, Medium Frequency transformer, Bio-inspired algorithm, Solid State Transformer, Isolated DC-DC Converter.

Balakrishnan Sridhar, Vadlamudi Syambabu
Analysis of Watermarking Techniques in Multimedia Communications
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DOI: https://doi.org/10.2298/SJEE2103321S
Abstract: Multimedia information is critical of examining, information perceived and which are illustrated by the human cerebrum. In our brain, 33% of the cortical area concentrates only on visual information processing. Digital watermarking technology is being received to guarantee and encourage such kinds of digital data authentication, security, and copyright. These algorithms permit the expandable values of different techniques to prevent the problems of copyright issues during the transmission. This paper discusses the detailed about the point by point investigation of watermarking definition and different watermarking applications and strategies used to improve information security.
Keywords: Digital watermarking, Confidentiality, Authenticity, Integrity, DWT, SVD.

Boris Georgiev Velev, Ivan Stoyanov Ivanov, Vladimir Vasilev Kamenov
Experimental Study and Thermal Analysis of Cooling Systems for Brushless Motors with Double Stator and Axial Gap
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DOI: https://doi.org/10.2298/SJEE2103333V
Abstract: The results of experimental research and thermal analysis of several types of cooling of brushless electric motors with nominal power 10-12kW (PMAC), suitable for “light” EV/HEV vehicles are presented in the research paper. The studied motors have permanent magnets, a double stator and an axial magnetic flux with air or liquid cooling. The Motor-CAD software performed the presented thermal analysis. The experimental study was made on the basis of precision results, obtained from the measurement of process temperatures during operation in a real-world environment. For this purpose, the electric motors were equipped with a number of thermocouples with which the temperatures are measured. The precise measurement and recording of the heat flux temperatures is performed using LabVIEW software. The calculations from the thermal analysis coincide with the experimental results and can be used to predict the heat fluxes in different designs and types of cooling systems. The possibilities for improving the cooling and power of standard PMAC electric motors with double stators have been studied and analyzed.
Keywords: Thermal analysis, EV/HEV – electric and hybrid vehicles, PMAC – brushless electric motor with permanent magnets, GUI – graphical user interface.

Noureddine Bouarroudj, Thameur Abdelkrim, Maissa Farhat, Vicente Feliu-Batlle, Boualam Benlahbib, Djamel Boukhetala, Fares Boudjema
Fuzzy Logic Controller Based Maximum Power Point Tracking and its Optimal Tuning in Photovoltaic Systems
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DOI: https://doi.org/10.2298/SJEE2103351B
Abstract: Conventionally, the parameters of a fuzzy logic controller (FLC) are obtained by a trial and error method or by human experience. In this paper, the problem of designing a FLC for maximum power point tracking (MPPT) of a photovoltaic system (PV) that consists of a PV generator, a DC-DC boost converter and a lead-acid battery is studied. The normalization gains, the membership functions and the fuzzy rules are automatically adjusted using a particles swarm optimization algorithm (PSO) in order to maximize the criterion based on the integration of the PV module power under standard temperature condition (STC) (T=25ºC and S=1000 W/m2). The robustness test of the optimized fuzzy logic MPPT controller (FLC-MPPT) is carried out under different scenarios. Simulation results of the system clearly show that the proposed optimized FLC-MPPT controller outperforms in terms of maximum efficiency the FLC-MPPT controller not optimized, the FLC-MPPT controller with optimized normalization gains and the FLC-MPPT controller with optimized normalization gains and membership functions.
Keywords: PV system, Boost converter, MPPT, FLC, FLC-MPPT, PSO, FLC-MPPT-PSO.

Zaw Myo Lwin, Thae Su Aye
A Rhomboid-shaped Printed Monopole Antenna for Wideband Circular Polarization
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DOI: https://doi.org/10.2298/SJEE2103385L
Abstract: This paper presents the design of a wideband circularly-polarized printed monopole antenna with a rhomboid shape. The rhomboid-shaped patch is fed by a microstrip line offset from the center to generate circular polarization (CP). The ground plane configuration is optimized for wide bandwidth operation. Bandwidth (satisfying both 10-dB return loss and 3-dB axial ratio) of 76% (1.92–4.27 GHz) is achieved in this research. The size of the proposed antenna is 0.386 (55×66 mm2) where λ02 is the free space wavelength which corresponds to the center frequency of the bandwidth. The antenna has a fractional bandwidth-size ratio (BW/size) of 1.97 which is higher than most CP monopole antennas in the literature. This antenna is suitable for Wi-Fi, WiMAX, and other wireless applications which outperform using circular polarization.
Keywords: Circular polarization, Printed monopole antenna, Rhomboid shape, Wideband antenna

Dejan Dašić, Miljan Vučetić, Nemanja Ilić, Miloš Stanković, Marko Beko
Application of Deep Learning Algorithms and Architectures in the New Generation of Mobile Networks
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DOI: https://doi.org/10.2298/SJEE2103397D
Abstract: Operators of modern mobile networks are faced with significant challenges in providing the requested level of service to an ever increasing number of user entities. Advanced machine learning techniques based on deep architectures and appropriate learning methods are recognized as promising ways of tackling the said challenges in many aspects of mobile networks, such as mobile data and mobility analysis, network control, network security and signal processing. Having firstly presented the background of deep learning and related technologies, the paper goes on to present the architectures used for deployment of deep learning in mobile networks. The paper continues with an overview of applications and services related to the new generation of mobile networks that employ deep learning methods. Finally, the paper presents practical use case of modulation classification as implementation of deep learning in an application essential for modern spectrum management. We complete this work by pinpointing future directions for research.
Keywords: Deep learning, Mobile networks, Mobile data analysis, Network security, Drone-based communications, Signal processing, Modulation Classification.



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