ECTI Transactions on Electrical Engineering, Electronics, and Communications

The Estimation of Breakdown Voltage of Vegetable Oil using Support Vector Machine

Supriyo Das, Adnan Iqbal — Thu, 27 Jun 2024 00:00:00 +0700

Oil as an insulating medium is widely used in power apparatus and it is important to have knowledge about its breakdown characteristics. Support Vector Machine (SVM) can be a fruitful tool for breakdown voltage (BDV) estimation. In this work, the objective is to explore the application of Support Vector Machine (SVM) to estimate breakdown voltage. Experiments are carried out on vegetable oil to obtain its breakdown voltage using Weibull distribution. Further, the experiments are done for different electrode gap and electrode shape. The experimental results are fed to SVM to train, test and estimate BDV. At the breakdown condition, the electric field features are extracted from the simulated electric field distribution. The electric field features are processed using Principal Component Analysis (PCA) to obtain the significant electric field parameter that contributes to breakdown characteristics of the oil medium. The output of PCA is used to construct a classification model to predict breakdown voltage by Support Vector Machine (SVM). The optimum value of SVM parameters are obtained using grid search and K – fold cross validation technique. The tuned SVM model is used to estimate the breakdown voltage of the oil medium under different electrode gap and shape. It is seen that the estimated BDV fairly matches with the experimental results. This shows the significance of using electric field features to predict breakdown voltage using SVM.

Technical Indices Evaluation of Radial Distribution Network with Optimally Allocated DGs and Capacitors

Rampreet Manjhi, Deepak Kumar Lal, Sandeep Biswal, Almoataz Y. Abdelaziz — Thu, 27 Jun 2024 00:00:00 +0700

Electric power distribution system planning is a key area of concentration for developing more efficient, trustworthy, and environmentally friendly energy sources in the future. While distributed generations (DGs) are excellent at reducing system actual power losses, shunt capacitors can supplement their effectiveness when utilized in tandem. It is feasible to achieve even higher reductions in power losses and enhanced system efficiency by combining DGs with shunt capacitors. The Loss Sensitivity Factor (LSF) measures how sensitive real power loss in a network is to changes in power injection (active or reactive power) at a single bus. The methodology analyses LSFs to assess the ideal sites for placing DGs and capacitors in radial distribution networks (RDNs). The Golden Jackal Optimization (GJO) strategy is adopted to discover the ideal sizing and allocation of DGs and capacitors. The strategy is tested using two RDNs, one with 33 buses and the other with 69 buses. In addition, five major technical indices are explored and examined, used as an evaluation criterion to distinguish between the optimal and baseline performances. These are the voltage deviation index (VDI), power loss index (PLI), fast voltage stability index (FVSI), line stability factor (LQP), and novel line stability index (NLSI). Voltage deviation, power loss, and voltage stability analysis-related indices are among the technical characteristics addressed.

Comprehensive Survey on Fault Detection and Classification in Three-Phase Induction Motors

Deepak Sonje, Ravindra Munje — Thu, 27 Jun 2024 00:00:00 +0700

Electric motors have revolutionized the way of human living and resulted in the modern lifestyle. These motors often operate in corrosive and dusty places and are exposed to a variety of undesirable conditions and situations that result in the failure of the motor. The faults occurring in Induction Motors (IM) need to be detected at a proper time for avoiding losses and further consequences. A well-designed fault detection scheme not only reduces motor failure but also increases productivity and even sometimes avoids accidents. This paper presents a review of fault detection and classification techniques in three-phase induction motors (TPIM). The main theme of this paper is to revisit the conventional methods for fault detection in TPIM and compare them with recently published methods based on parameters to be sensed, and the type of fault that can be detected, with their advantages and drawbacks. Around a hundred papers are critically reviewed and studied from old and new regimes. Attention is also given to fault detection methods based on artificial intelligence (AI) and machine learning (ML). This paper concludes with brief remarks which will be very useful for new researchers who are willing to research in the domain of fault detection and classification.

Assessments of Power Systems Voltage Stability Considering Transmission Line Security

Dumrongsak Wongta, Sermsak Uatrongjit, Chawasak Rakpenthai, Nattapong Pothi — Thu, 27 Jun 2024 00:00:00 +0700

This paper presents two indicators, namely line voltage stability and line ampacity indices, to determine the voltage stability states and line security of power systems under various operating conditions. Both indices rely on the measured values that are already obtained from conventional measurements used in power systems. The identification of weak buses and critical lines based on the proposed indices is possible using only voltage magnitude and real power measurements. To validate the effectiveness of the proposed indices, two power networks have been tested under increasing system loading and line outage conditions. Numerical experimental results indicate that by considering both line voltage stability and line ampacity indices, power systems could mitigate the risks of voltage collapse and excessive current in transmission line.

Performance Analysis of Distance-Based Wireless Transceiver Placement for Wireless NoCs with Deterministic Routing

Thu, 27 Jun 2024 00:00:00 +0700

This research analyzes the impact of wireless transceiver subnet clustering on a hundred-core mesh-structured WiNoC architecture. The study aims to examine the
effects of distance-based wireless transceiver placements on transmission delay, network throughput, and energy consumption in a mesh Wireless NoC architecture with a hundred cores, particularly under the X-Y, West-First, Negative-First, and North-Last routing strategies. This research investigates the impact of positioning radio subnets at the farthest, farther, nearest, and closest positions within an architecture featuring four wireless transceivers. The Noxim simulator was used to simulate the analyzed wireless transceiver placements on the hundred-core mesh-structured WiNoC designs, with the objective of validating the results. The architecture with the wireless transceiver positioned at the midway proximity (nearer and further) delivers the best performance, as evidenced by the lowest latencies for all evaluated deterministic routing algorithms, corresponding to the simulation outcomes.

Minimal Realization Plus Current Output CC-based Biquad Circuit

Sompong Wisetphanichkij, Krit Angkeaw, Napat Sra-ium — Thu, 27 Jun 2024 00:00:00 +0700

This paper presents a minimal design of a biquad circuit using only one plus current output type-II current conveyor (CCII), one differential voltage current conveyor (DVCC) and grounded passive components. The circuit enables the implementation of all 5 basic filter types: low-pass (LP), band-pass (BP), high-pass (HP), band-stop (BS) and all-pass (AP) by the selecting and adding of the input and output currents with no component matching constraints. Moreover, the circuit parameters ω₀ and Q can be set simply by adjusting the circuit components. The proposed biquad circuit performance has very low sensitivity to circuit components due to its simple structure and a small number of devices (2 active and 4 grounded passive components). This allows the circuit to work at high frequencies. The performance of the proposed topology was evaluated through PSPICE simulator using the 0.18 mm CMOS technology from the Taiwan Semiconductor Manufacturing Company (TSMC).

Performance Evaluation of Free Space Optic (FSO) Technology Using PPM and OOK Modulation

Thu, 27 Jun 2024 00:00:00 +0700

The increasing trend in developing free space optic (FSO) system technology, which is expected to become an alternative for future high-speed wireless communications based on optical communication system, demands comprehensive performance observation of propagation parameters. So, this research proposes an FSO system model using pulse position modulation and on-off keying modulation by considering the influence and reliability of the system on distance, atmospheric conditions, and variations in aperture diameter. The test results include the bit error rate (BER), Q-factor, and optical and electrical signal-to-noise ratio (OSNR/ESNR) at a bit rate of 2.5 Gbps. Based on result observations of the reliability of the FSO system using PPM and OOK modulation at a bit rate of 2.5 Gbps and an optical lens diameter of 5 cm, the proposed system model is capable of meeting optical communication standards up to a transmission distance of 1 km. Meanwhile, in testing various atmospheric conditions with an optical lens diameter of 5 cm to a distance of 0.5 km, the system model is suitable for use in light fog, very light fog, and light mist to clear air conditions. However, in this test scenario, the system is not feasible for dense, thick, and moderate fog conditions. Furthermore, observations at a distance of 0.5 km show that by increasing the optical lens aperture diameter from 20 cm to 30 cm, the proposed system model can achieve BER values of less than 10^-30 to 10^-12 in thick fog conditions. In general, there is no significant difference between system performance, including BER, Q factor, and OSNR and ESNR values, whether using PPM modulation or OOK modulation, where the use of a wavelength of 1330 nm is more recommended than 1550 nm judging from the selected signal to noise ratio value.

A New Single-Source Switched-Capacitor Based Seven-Level Boost Inverter Topology with Reduced Part Count and Voltage Stress

Kasinath Jena, Dhananjay Kumar — Thu, 27 Jun 2024 00:00:00 +0700

The use of multi-level inverters is a widespread and effective solution for solar power plants, wind farms, and other types of renewable energy sources. A novel switched-capacitor multi gain inverter topology (SCMGIT) is proposed in this paper. The research presents a SCMGIT that, with a single dc source, can produce seven distinct voltage levels at a voltage-boosting of three times the original input. The proposed SCMGIT exhibits several noteworthy characteristics, including self-balancing capacitor voltages, fewer switches with decreased voltage stress, and bipolar voltage generation without the usage of a backend H-bridge. A thorough comparison with other SC inverter has been performed in the article to highlight the benefits of the suggested SCMGIT. An analysis of the proposed SCMGIT has been investigated, and verified by simulation and experimental testing with a low prototype.

Whale Optimization Algorithm Based Closed-Loop Control Z-source inverter for Wind Energy Application

Sweta Kumari, Dr. — Thu, 27 Jun 2024 00:00:00 +0700

In this paper, an enhanced 0.5 kW Z-source inverter (ZSI) model is used in the design of a wind energy generating system (WEGS) that uses a 1.2 kW wind turbine to overcome the operating restrictions of the traditional ZSI model. To achieve a constant line-to-line voltage with varying loads at the output side of the WEGS, a closed-loop control technique is applied at the load side. A proportional-integral (PI) controller is utilised with the ZSI for closed-loop control since it is the least complicated in terms of tuning and operation. Also, ZSI systems have nonlinear behaviour, which precludes direct application of the PI controller technique to them. As a result, the novelty of this article is the optimisation of stabilised PI coefficients (Kp, Ki) with a modified ZSI model. Particle swarm optimisation (PSO), sine-cosine algorithm (SCA), and whale optimisation algorithm (WOA)-based optimisation techniques are used to handle PI tuning for closed-loop modified ZSI. In terms of the stability of the closed-loop modified ZSI with WEGS, the WOA performs better. The outcomes show that the suggested controller can control the variation in AC output voltage of ZSI with variable load exactly.

A new high step-up single switch DC-DC converter with soft switching on all semiconductor elements

mahmood vesali — Thu, 27 Jun 2024 00:00:00 +0700

This paper presents a high step-up DC-DC converter. The converter has a simple structure and without adding any auxiliary switch, soft switching condition is provided in the converter. Due to the fact that any switch is not added to the converter, there is no need to design a new control circuit for this converter and the basic control circuit structure is suitable for this converter. In the proposed converter with minimum number of auxiliary elements soft switching condition provides, which in addition to have a simple structure, reduces losses and increases efficiency. soft switching condition is provided under zero current switching (ZCS) when switch is turned on and under zero voltage switching (ZVS) when the switch is turned off. The voltage stress on the switch is at a lower level than the output voltage of the converter, which the switch can use with low voltage. Also, not much current stress is imposed on the switch, which does not require a very high current switch. The proposed converter has been completely analyzed and in order to prove the theoretical analysis, the converter is implemented at a power of 500 watts and at a full load the efficiency of about 97.2% is obtained.

Edge-based Federated Learning to Enhance the Security of IoT

zahra eskandari — Thu, 27 Jun 2024 00:00:00 +0700

The integration of Artificial Intelligence (AI) and Internet of Things (IoT) has enabled network components to make independent decisions, but this capability also poses a risk of malicious attacks in unsupervised and trustless environments. To overcome this issue, the article proposes a distributed collaborative detection approach that utilizes edge nodes as voters to monitor the training process, tackle PA, and improve the accuracy of the global model. The proposed approach isevaluated using the UNSW-NB15 dataset in both IID and non- IID scenarios, and the results demonstrate the effectiveness of the approach in improving the accuracy of FL even in the presence of PA.

A Novel adaptive neuro-fuzzy control scheme for eliminating rule explosion in dynamic systems

Ashwani Kharola — Thu, 27 Jun 2024 00:00:00 +0700

This article presents a neuro-fuzzy adaptive control scheme for avoiding the problem of rule explosion inherently associated with fuzzy control systems. The study proposes a novel neuro-fuzzy model designed using only two membership functions and four if-then fuzzy rules for control of highly nonlinear two-stage cart and pendulum system. The neuro-fuzzy controller has been designed with the minimum possible number of rules thus solving the problem of rule explosion completely. The study further compares proposed ANFIS controller with conventional proportional-integral-derivative (PID) and artificial neural network controllers in terms of settling time, overshoot ranges and steady state error. The results show better performance of ANFIS controller compared to PID and neural controllers.

Classification of Vibration in Coal Mining Industry via Deep Neural Network

Jirasak Thothong, Kanok Charoenchaiprakit, Wekin Piyarat, Kampol Woradit — Thu, 27 Jun 2024 00:00:00 +0700

Recently, the electricity from coal mining industry is still necessary because it serves as a primary electrical source in many areas in response to high demand in power. However, coal mining can harm the miners, environment, and villages near mining site due to ground vibration from blasts during the operation. Hence, every coal mine industry is required to report the ground vibration for safety purposes. Mostly, the ground vibration data comes from the vibration sensors deployed around the mining site, and the vibration data will be sent to the control room. Due to tons of the vibration data, operators have difficulty in classifying the blast vibrations from the records which causes time-consuming and possible human errors during process. To solve these problems, this article proposes the Deep Neural Network (DNN) model for a blast vibration classification with 3 hidden layers. the ground vibration data used in training and validating the DNN are collected by the Mae Moh mine site in Thailand. As the result, the designed DNN meets the standard with the accuracy of 100%.

A Novel Target Detection and Identifying Approach Using Polarimetric Radar Cross-Section and Matrix Correlation Coefficient

Narathep Phruksahiran — Thu, 27 Jun 2024 00:00:00 +0700

This paper presents a novel target detection and identifying approach using polarimetric radar cross-section and matrix correlation coefficient. We have adopted a polarimetric radar cross-section matrix correlation strategy (PRMC) algorithm using a matrix correlation approach based on the polarimetric radar cross-section. It is projected as an inverse scattering problem under the electromagnetic scattering model using polarimetric Physical Optics approximation. The experimental measurements using canonical targets carried out under semicontrolled conditions verify the performance of the developed procedures. Finally, the identification strategies' effectiveness is demonstrated in free-space conditions and a scene with a brick and autoclaved aerated concrete wall.

Radio Tomography Imaging using Adjacent Criterion Method to determine the Localization Error

Thu, 27 Jun 2024 00:00:00 +0700

Observed that most setups have limitations in the number of RF nodes due to a limited number of measurements. However, it is well known that the main difficulty in radio tomographic imaging attributes to the uncertainties in the receive signal strength (RSS) measurements of transceivers due to multipath effects, especially, when the environment of interest is much cluttered, and requirements on the larger number of nodes for the performance improvements. However, no study has been conducted to solve the inverse problem and improve the quality of the reconstructed image using a reduced sensor model for Radio tomography system localization.
This work focuses on the design and development of a Radio tomography system for human localization that will employ a transceiver sensor arrangement to increase the number of measurements, without making any changes to the hardware design as well as the number of pixels in the sensing domain. An image reconstruction technique namely, Adjacent Criterion Method (ACM) was proposed to enhance the image spatial resolution. A number of experiments were used to evaluate the performance of the system. The results showed that the proposed technique improves the spatial resolution and exhibits more accurate tomograms