Electrical & Electronics Engineering

Permanent URI for this collectionhttp://197.211.34.35:4000/handle/123456789/65

Electrical & Electronics Engineering

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Start date: 2020End date: 2024

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Now showing 1 - 10 of 11
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    Comparative Analysis of Machine Learning Algorithms for Eccentricity Fault Classification in Salient Pole Synchronous Machine
    (IEEE, 2024-03-22) Shejwalkar, Ashwin; Yusuf, Latifa; Ilamparithi, Thirumarai Chelvan
    The paper performs a comparative study of Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs) for the classification of Static Eccentricity (SE) and Dynamic Eccentricity (DE) faults in a Salient Pole Synchronous Machine (SPSM). The SPSM was subjected to varying SE and DE severities, unbalanced source voltages, and load conditions. Stator and field current data were measured, and various time-domain and frequency-domain features were extracted from the above-mentioned data. Both networks were fed these features and compared based on classification accuracy, robustness, and computational complexity.
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    Deployment of an Electronic-based Approach for Fruits Juice Ingredient Analysis
    (International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG) Landmark University, 2024-04-04) Kufre Esenowo Jack; Lanre Joseph Olatomiwa; Yahaya Asizehi Enesi; Grace Idowu Olaleru; Nnaemeka Emmanuel Ugwuogor; Babawuya Alkali
    This paper considers the deployment of an electronic-based fruits juice ingredient analysis. Most of the fruits juice products available in the market now contain water in large quantities than the active ingredients. This design attempts to respond to the end user's complaints. By putting on this design, it is expected to serve as a quality check and control for our teeming enterprising fruit substance producers. The system was designed and simulated using proteus and implemented using hardware electronic components. The system uses an infrared transmitter, fruit sample handler, and infrared receiver to realize its design. The instrument was calibrated with natural pineapple juice with 60% of water content. The outputs of this device were displayed using a cathode ray oscilloscope and voltmeter respectively. Five different samples of fruit juice were analyzed namely: A, B, C, D, and E. Results showed that all fruit juice contains a reasonable quantity of water which is not regarded as an adulteration since it is the natural content of the fruit. However, water content above 60% may be considered as much. It is recommended that fruit juice producers employ this system for their quality and control checks. Moreover, further research should take into consideration, the colour and viscosity of different fruit juices with a view to seeing how the system can analyze them, while the output should incorporate a microcontroller for an intelligent analysis and digital display.
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    Pulse Width Modulation Analysis of Five-Level Inverter- Fed Permanent Magnet Synchronous Motors for Electric Vehicle Applications
    (International Journal of Robotics and Control Systems, 2021-11-21) Omokhafe J. Tola; Edwin A. Umoh; Edwin A. Umoh
    n recent times, intense research has been focused on the performance enhancement of permanent magnet synchronous motors (PMSM) for electric vehicle (EV) applications to reduce their torque and current ripples. Permanent magnet synchronous motors are widely used in electric vehicle systems due to their high efficiency and high torque density. To have a good dynamic and transient response, an appropriate inverter topology is required. In this paper, a five-level inverter fed PMSM for electric vehicle applications, realized via co-simulation in an electromagnetic suite environment with a reduced stator winding current of PMSM via the use of in-phase disposition (PD) pulse width modulation (PWM) techniques as the control strategy is presented. The proposed topology minimizes the total harmonic distortion (THD) in the inverter circuit and the motor fed and also improves the torque ripples and the steady-state flux when compared to conventional PWM techniques. A good dynamic response was achieved with less than 10A stator winding current, zero percent overshoot, and 0.02 second settling time synchronization. Thus, the stator currents are relatively low when compared to the conventional PWM. This topology contribution to the open problem of evolving strategies that can enhance the performance of electric drive systems used in unmanned aerial vehicles (UAV), mechatronics, and robotic systems
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    Design and Implementation of Real Time Internet of Things (IoT) Enhanced Irrigation System
    (El-Amin University Journal of Computing (EAUJC), 2024-04-01) J. A. Ojo; Ajiboye, Johnson Adegbenga; M. A. Ajiboye; D. J. Ajiboye; H. O. Ohize; A. A. Isa
    Irrigation is a practice that has existed for a long time. Irrigation is the process of supplying water to the soil during drought or unfavourable weather conditions. Over the years, irrigation practices have evolved in order to eliminate the risk of manual irrigation. This risk includes over irrigation, under irrigation, erosion among others. Modern irrigation practices aim to reduce these problems by incorporating sensor technology, Internet of Things (IoT) and automations. The aim of this work is to design and a Real-Time IoT enhanced irrigation system which utilizes data about the condition of the environment to automate the irrigation process. This system makes use of soil moisture sensor, a rain sensor and a temperature and humidity sensor to capture real time environmental data and makes logic decisions based on the collected data. An ESP 32 microcontroller functions as the brain of the system by collecting data from the sensors and controlling the pump accordingly. The system also employs lot technology using Arduino Cloud loT platform in order to provide remote accessibility. The experimental evaluation involved subjecting the irrigation system to two distinct soil conditions; one dry and the other wet. The results demonstrate the functionality of the system: when rain sensor readings fall below the set threshold of 30% and soil moisture sensor readings drop below 15%, the irrigation pump is activated to compensate for the lack of rainfall and soil moisture. Furthermore, the system responds to environmental conditions, activating the pump for an extended period when relative humidity is below 60% and the temperature exceeds 25°C. Conversely, when the soil is already wet, indicated by high soil moisture sensor readings, the pump remains permanently turned off. This automated irrigation system showcases the potential to optimize water usage and enhance efficiency in response to dynamic environmental factors.
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    DEVELOPMENT OF MODEL METRICS FOR INDIVIDUALS AND PAIR PROGRAMMERS AMONG SOFTWARE DEVELOPERS IN AN AGILE ENVIRONMENT
    (2023) Ajiboye M.A; Ajiboye, Johnson Adegbenga; Audu W.M; Ajiboye D.J; Ohize H.O; Majin R.N; Abolarin M.S
    In this work, maintainability as a function of time to correct codes was examined among various categories of software developers. Deliberate errors, ranging from two to ten, were introduced into sets of agile codes written in python programming language and given to 100 programmers each in the groups of Individual Junior, Individual Expert, Random, Expert pairs, junior pairs and Junior Expert pairs. The time spent to correct the errors was analysed using regression model for prediction. Bivariate correlation was used to check the relationships between the number of bugs in projects and the time spent to correct the errors. The correlation between the number of bugs and time of debugging was highly significant, strong and positive. This revealed that the time spent in correcting system software errors increased significantly as the number of bugs increased. Linear, logarithmic, inverse, quadratic, cubic and exponential regression models were used to generate metrics with time spent on error as dependent variable and number of bugs as independent variable for each of the pair and individual programmers. On the average, cubic model gave the highest R2 value of 0.639 in comparison to other models. Therefore, Cubic model gave the best fit as it explains the patterns of the relationship between the dependent and independent variable most appropriately.
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    Comparative Analysis of Macro Femto Networks Interference Mitigation Techniques
    (IJWMT, 2022-12-20) Katfun Philemon Dawar; Abraham U. Usman; Bala Alhaji Salihu; Michael David; Supreme Ayewoh Okoh; Ajiboye, Johnson Adegbenga
    When interference is reduced, the benefits of using a macrocell and femtocell heterogeneous network (Macro-Femto) heterogeneous network (HetNet) can be increased to their full potential. In this study, Enhanced Active Power Control (EAPC), Active Power Control (APC), and Power Control (PC1) interference mitigation strategies are applied, and their performances in uplink and downlink transmission of 5G Non-Stand-Alone (NSA) architecture are compared. According to the findings of a MATLAB simulation, the EAPC technique utilized a lower amount of transmit power for the Macro User Equipment (MUE), the Home User Equipment (HUE), and the femtocell logical node (Hen-gNB), in comparison to the APC and PC1 techniques. While PC1 approach required less en-gNB transmission power. The MUE, HUE, hen-gNB, and en-gNB throughput of the EAPC approach was much higher. This work will enable wireless system designers and network engineers know the appropriate technique to utilize to achieve desired Quality of Service (QoS) while conserving network resources
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    DSP in Communication Engineering - A Review
    (I3C 2024, 2024-04-22) Ajiboye, Johnson Adegbenga; Jiya Z.J; Paul M.; Ajiboye M.A; Ajiboye D.J; Majin R.N
    This paper provides a comprehensive review of Digital Signal Processing (DSP) in communication engineering, elucidating its fundamental principles, practical applications, and recent advancements. Beginning with an overview of DSP's distinguishing features and historical evolution, the paper delineates its pivotal role in processing real-world signals, including speech, image, and seismic data. Furthermore, the introduction of Software Defined Radio (SDR) is examined, underscoring its transformative impact on communication systems by enabling dynamic spectrum access and multi-standard operation through DSP algorithms. Additionally, the emergence of Quantum Signal Processing is explored, highlighting its significance in secure communication through Quantum Key Distribution (QKD) and Quantum Error Correction. Despite the benefits offered by DSP, challenges such as computational complexity and signal distortions are addressed, emphasizing the need for advanced techniques and algorithms to mitigate these issues. Ultimately, this paper elucidates DSP's enduring relevance and innovation in shaping the future of communication engineering.
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    Glare Stopper: The Automatic Car Headlight Management System
    (2023-03-22) Abdullahi Daniyan, Samuel S. Ilupeju
    The growing number of vehicles on roads calls for increased safety considerations, especially during night driving. A common issue is the misusage of high beam headlights, which can cause light glare for opposing drivers due to the high intensity beam a driver receives from oncoming vehicles. This is called the Troxler Effect. This is a safety critical issue given that the human eyes are very sensitive to light, and when eyes suddenly encounter high intensity light, one’s vision get temporarily affected and require some time to recover the vision. During this vision recovery window, the vehicle has covered some distance which could increase the likelihood of an accident occurring. To address this, we propose an automatic car headlight management system that adjusts a vehicle’s headlights based on light intensity of oncoming vehicles. The system utilizes an Arduino Uno microcontroller and an LDR sensor installed on the driver's side to detect light levels of at least 700 lumens. The microcontroller then sends a command to a relay, which switches the headlights from high beam to low beam. Results demonstrate effective performance of the proposed system in terms of achieving faster switching time and consuming lower power.
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    A Face Recognition-Based Intruder Detection System for Automatic Door Control
    (IEC, 2023-03-21) Abdullahi Daniyan, Michael O. Michael
    In recent years, theft and unauthorized access to private areas in homes and communities has become a growing concern, leaving individuals feeling insecure about their lives and properties. To address this problem, this paper proposes a solution that features a facial recognition system to prevent entry by unauthorized individuals. The system uses an ESP32 Camera module and the Arduino Integrated Development Environment (IDE) to capture and store facial biometric details through facial recognition techniques. The data is saved in a database that is accessible through a web interface enabled by HOTSPOT connection. The camera's Internet Protocol (IP) address also allows for live streaming as an added feature. An ATmega328 microcontroller on the Arduino IDE receives signals from the ESP32 camera, process the data and operate the door accordingly. When the ESP32 Camera recognizes a face, it sends a signal to the microcontroller to open the door. If the face is not recognized, the door is kept locked to prevent entry by intruders. The proposed solution effectively identifies intruders and those with authorized access but grants access only to authorized individuals in its database. This ensures a secure environment for homes and communities, providing peace of mind to individuals who have long been worried about theft and unauthorized access. Results demonstrate that the proposed facial recognition system is has been able to provide a secure environment for homes and communities by denying entry to intruders and granting access only to recognized individuals.
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    Enhanced Kinetochore Detection During Mitotic Human Cell Division using CFAR
    (IEEE, 2024-10-11) Abdullahi Daniyan; Alessio V. Inchingolo; Andrew McAinsh; Nigel Burroughs
    In this paper, we present an innovative application of the Constant False Alarm Rate (CFAR) algorithm, traditionally utilized in radar signal processing, to enhance the accuracy and reliability of kinetochore (KT) tracking in live-cell lattice light-sheet microscopy (LLSM) imaging of human cells during the mitotic phase of cell division. Fluorescently labelled KTs appear as spots in diffraction-limited light microscopy. Traditional KT detection methods, such as adaptive thresholding, often struggle with the dynamic and noisy backgrounds of cells, leading to less efficient KT identification. By adapting the CFAR algorithm to the specific challenges of KT detection in 3D, we present a method that offers improved precision and stability in detecting KTs across different stages of mitosis. The performance of the CFAR-KT method was rigorously compared to the adaptive thresholding approach across a cohort of 31 cells, with results highlighting CFAR-KT’s enhanced detection efficiency. Despite a slightly lower mean detection count compared to the adaptive method, the CFAR-KT method achieved lower false positives and a higher success rate in tracking KTs over the duration of the cell division process, underscoring its effectiveness in capturing the dynamics of KTs.