Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
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Simple and Efficient Key Management Method for Hierarchical Wireless Sensor Networks
Full text linkSecurity is an important consideration for Wireless Sensor Networks (WSNs), and key management plays a pivotal role in facilitating safe communication and data transfer. Key management must be designed with the constraints of these networks in mind, which include limited computation capabilities, memory, and energy. Achieving secure and efficient communication in large-scale WSNs is a significant challenge. In this paper, we propose a simple key management method for securing hierarchical WSNs, which employs only a few hash functions and XOR operations to derive shared keys. Its simplicity makes optimal use of resources and offers an efficient approach to establishing keys for sensor nodes. Simulation results demonstrate that the proposed scheme reduces energy consumption by 15% and decreases the key establishment time by 20% compared to existing methods such as LKMS, while maintaining strong security with low computational and communication costs, which are crucial considerations for WSNs
Diagnosis and Monitoring Method for Detecting and Localizing Bearing Faults
Full text linkInduction motors in modern industry are becoming more and more functional and complex. Unfortunately, these machines are not free from damages what make their fault diagnosis the most critical aspect of system monitoring and maintenance. Vibrational signal data yields relevant information about the state of the entire system, as well as specifically about one of its components that makes its analysis quite interesting. For this effect, the current paper aims to propose an automatic diagnosis and monitoring method for detecting and locating bearing faults in an induction motor based on vibration signal processing. The suggested method combines the discrete wavelet transform (DWT) with the envelope spectrum (ENV) as advanced signal processing, incorporating a machine learning algorithm based on random forest classifier. The discrete wavelet transforms (DWT), using the Haar wavelet, decomposes the vibrational signal to provide both approximations and details. Each detail is then reconstructed to avoid any missing of information. To precisely select the reconstructed detail () that provides pertinent information about bearing faults, a statistical study is conducted. This study involves calculating four indicators (Root mean square (RMS), correlation coefficient (CC), energy coefficient (EC) and peak to peak (P2P) factor) is performed for each (). These indicators are compared with threshold indicators, and this criterion is met by the reconstructed details 1 and 3. The obtained reconstructed details are then subjected to the spectral envelope analysis to detect the fault frequencies, which are considered as new features entering the random forest classifier model. This combination of approaches allows better feature extraction and structuring of the dataset, leading to improved accuracy of the random forest classifier, achieving a higher classification rate of more than 99,53 %. The proposed DWT-ENV-RF method indicates well its efficiency when compared to other recent works, and the attained results are all confirmed by the experimental tests conducted in the CWRU laboratory
Enhancing indoor radio tomographic imaging based on minimum RF nodes
No full textUses the attenuation on the links between transceivers to produce an image using Radio Tomographic Imaging (RTI), a network of transceivers, or a Wireless Sensor Network (WSN). Several RTI setups have been constructed as monitoring areas. However, it is 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 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 improvement. It is highly remarkable that the motivation of using fewer nodes in this work is to reduce the deployment cost of radio tomographic imaging, slower data collection rates, longer imaging reconstruction times, and bigger sensitivity matricest, this lead author to proposed to design and development of an RTI system with a minimum of 8 RF nodes. The strong and weak received signal strength (RSS) exhibited in the images will be used to assess the effectiveness and accuracy of human sensing localization in a region. The images were reconstructed based on selected image reconstruction algorithms, and they are Linear Back- Projection (LBP), Filtered Back Projection (FBP), Gaussian, Newton’s One-step’s Error Reconstruction (NOSER) and Tikhonov Regularization (TR). The reconstructed images will be analysed using the Mean Structural Similarity (MSSIM) index. A comparison between the algorithms mentioned RTI system based on the MSSIM index. NOSER and TR algorithms scored the highest for the MSSIM index overall experiments, and it is the best technique to produce images that appear similar to the original images
Ant-Lion Optimization Algorithm Based Optimal Performance of Micro Grids
Full text linkIn the operational state of an electrical power system, ensuring efficient utilization and high-quality power usage is essential. Various quality enhancement measures, such as linear and adaptive filters, are implemented to improve the current's quality. Additionally, power flow controllers are employed to mitigate losses and enhance fault tolerance. However, the escalating demand for power supply, driven by rapid industrial and urban growth, often exceeds the capacity of existing generation systems. To address this challenge, supplementary subunits are integrated into the power system. This proposal's main objective is to introduce a weight-defined parameter monitoring system for power scheduling within a multi-parameter monitoring framework. The aim is to enhance the conventional preference-based scheduler by incorporating intelligent control techniques, including Unified Power Quality Conditioner (UPQC) with the ANT-LION Optimization (ALO) algorithm, which will be compared to a Fuzzy Logic controller. UPQC plays a pivotal role in addressing power quality issues within the system, combining a shunt active power filter with an Artificial Neural Network (ANN) controlled by the ALO algorithm. Our research demonstrates the effectiveness of this proposed system, particularly in microgrid applications, with validation conducted using MATLAB/Simulink.
A Simple Lyapunov Function Based Control Strategy for Coordinated Transient Stability Enhancement of Power Systems
Full text linkTransient stability is still a serious impediment in power system operation due to their highly nonlinear nature. Over the last decades, a vast number of diverse nonlinear control algorithms for sub-controllers located at the generator subsystem and transmission lines have been developed to boost power system stability. However, for an effective and feasible operation of these power systems, coordination of these sub-controllers is very essential. In this paper, a simple direct Lyapunov based approach for coordinated control is proposed for global enhancement of power system stability. The proposed control scheme is achieved through the coordination of Lyapunov based decentralized steam valve, excitation and SSSC adaptive controllers. To test the efficacy of the proposed scheme, several comparisons in multi-machine fault scenarios with other design coordinated approaches are presented. Numerical simulations demonstrate the swiftness and efficacy of the proposed control scheme in boosting global stability
Advanced Multimodal Emotion Recognition for Javanese Language Using Deep Learning
Full text linkThis research develops a robust emotion recognition system for the Javanese language using multimodal audio and video datasets, addressing the limited advancements in emotion recognition specific to this language. Three models were explored to enhance emotional feature extraction: the SpectrogramImage Model (Model 1), which converts audio inputs into spectrogram images and integrates them with facial images for emotion labeling; the Convolutional-MFCC Model (Model 2), which leverages convolutional techniques for image processing and Mel-frequency cepstral coefficients for audio; and the Multimodal Feature-Extraction Model (Model 3), which independently processes video and audio features before integrating them for emotion recognition. Comparative analysis shows that the Multimodal Feature-Extraction Model achieves the highest accuracy of 93%, surpassing the Convolutional-MFCC Model at 85% and the Spectrogram-Image Model at 71%. These findings demonstrate that effective multimodal integration, mainly through separate feature extraction, significantly enhances emotion recognition accuracy. This research improves communication systems and offers deeper insights into Javanese emotional expressions, with potential applications in human-computer interaction, healthcare, and cultural studies. Additionally, it contributes to the advancement of sophisticated emotion recognition technologies
A Compact Inset Coupled-Fed Triangular Patch Antenna For Wideband 5G Applications
Full text linkFor 5G applications, a compact inset coupled-fed high bandwidth triangle antenna is demonstrated. A large bandwidth can be achieved by combining the inset and coupling feeding with a triangle-shaped patch. With a VSWR of less than 2, the suggested antenna's working frequency of 3.6 GHz spans the frequency range needed for 5G applications, which is between 2.8 and 5.6 GHz. The primary characteristics of the suggested antenna are its smaller dimensions (20.5 × 17.5 mm2) and about 35% increased bandwidth. Significant factors that match the simulated results exactly are S11, radiation pattern, radiation efficiency, and peak gain in the proceeding of the proposed antenna. With the addition of two parallel rectangular strips with a triangular-shaped patch, the antenna is capable to achieve 40% reductions in size, 81.74% radiation efficiency, and 2.61 dB peak gain for the suggested antenna. With a center frequency of 3.6 GHz and a reflection coefficient of 28.6 dB, the fractional bandwidth is 66.67% (2.8 GHz to 5.6 GHz). With a smaller surface wave and an excellent omnidirectional radiation pattern, the antenna's inset coupling feeding arrangement makes it appropriate for Sub-GHz 5G applications.
Stabilizing Quadruped Robot Movement Using Fuzzy Logic Control for Yaw Angle Adjustment in Walking and Troting Gait
Full text linkBalance is a fundamental aspect of quadruped robots that determines their movement success. Imbalanced movement can affect the robot's orientation, leading to potential deviations from the intended direction due to changes in the attitude angle. An unstable attitude angle can result in loss of control, complicating effective navigation. This loss of control may prevent the robot from maintaining its stability, increasing the risk of falling. This study designs a control system for a quadruped robot using fuzzy control system to manage the yaw angle while the robot walks forward using both walking and trotting gaits. The fuzzy control system outputs are used to adjust the hip joint angles of the robot's four legs, modifying the stride length of each leg accordingly. The quadruped robot was tested with both walking and trotting gaits moving forward for 30 seconds. The quadruped robot successfully maintained balance and stability in the -axis (yaw) on a flat, obstacle-free surface using fuzzy control system. The fuzzy logic control effectively reduced positional distance fluctuations from the set point and enhanced the robot's ability to return to the set point after fluctuations, without producing excessive overshoot
Design of Solar Home Charging for Individual Electric Vehicles: Case Study for Indonesian Household
Full text linkThis study aims to examine the use of solar energy through Rooftop Photovoltaic (RPV) technology for solar-powered home charging of individual electric vehicles (EVs) in Indonesia. Simulations using HOMER Pro software are carried out to analyze both the energy and financial performance of the designed RPV system. According to the calculations, a 4 kW RPV system is required to meet the daily energy demand for EVs in the household sector. The off-grid RPV system design consists of 12 unit 325 wp PV panels, 36 units of 100AH battery as power storage, and a 4000-watt inverter to convert DC from RPV system into AC for battery charging. Simulation results from HOMER Pro software confirm that the designed RPV system can adequately supply the electricity needed for home charging, generating a total of 6449 Wh per year. With an annual energy consumption of approximately 4,190 kWh/year, the proposed system not only meets the daily energy needs of EVs but also provides excess power to be used by additional electrical equipment. Additionally, the proposed system can reduce 77.89 tons of CO2 emissions over the 25-year project lifespan
Optimal Power Flow with Integrated Large Scale PV Systems: Case of the Algerian solar field
Full text linkThe integration of large-scale solar-photovoltaic generation in the traditional power system complicates the optimal power flow (OPF) problem formulation. In the present paper, the OPF based on the quadratic and cubic fuel cost functions integrating solar energy potential of the south of Algeria is presented. Solar energy has a stochastic behavior described in the proposed methodology by the Beta probability distribution function (βPDF). The corresponding objective functions consider the penalty and reserve costs of large-scale solar-photovoltaic generations. The proposed OPF is solved by particle swarm optimization (PSO) algorithm. Computer simulations have been performed on an Algerian 59 bus test system considering some candidates solar energy source emplacements. The comparison between OPF solutions based on the two aforementioned cost functions has been established. The cubic fuel cost function case shows more environmental pollution reduction as well as satisfying interconnected power demands. Thanks to the PSO algorithm properties used for the OPF resolution, the Algerian solar field seems to be a good opportunity for large-scale solarphotovoltaic generation installations in an oligopolistic and eco-friendly sense