Theses (Department of Electrical Engineering and Mechatronics)
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Theses collection of the Faculty of Engineering.
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Theses (Department of Electrical Engineering and Mechatronics) Cím szerinti böngészés
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Tétel Korlátozottan hozzáférhető 24 GHz Fractal MPA Antenna Development For EMI Testing In RF Spectrum MeasurementDobariya, Kashish; Istvan, Balajti; DE--Műszaki KarSquare Fractal antenna designing using AutoCAD and MATLAB softwares. It resonates at a frequency of 24 GHz. The poposed antenna is designed with different number of iterations, the PCB antenna ready for fabrication is shown and the simulated results are compared with various types of fractal antenna.Tétel Korlátozottan hozzáférhető 4Ch VNA-Based In-Situ Measurement Techniques For Phased Array AntennasAli, Syed Arbaz; István, Balajti; DE--Műszaki KarThe thesis explores the use of a 4-channel Vector Network Analyzer (4ChVNA) for in-situ measurement of phased array antennas, crucial in wireless technology. It emphasizes the importance and challenges of in-situ measurement tools like VNA for accurate, immediate assessments. The research focuses on characterizing antenna elements in phased arrays, enhancing understanding of their behavior for IoT sensor antenna performance requirements. This involves employing specialized tools and devising effective measurement strategies. Additionally, it evaluates the frequency response of "L" band phased arrays, offering insights into their operating bandwidth and resonance. Ultimately, this work enhances existing knowledge and sets the stage for future developments in the field.Tétel Korlátozottan hozzáférhető AI-Powered Drone Integration for Obstacle AvoidanceAlTamimi, Jebril; Korsoveczki, Gyula; DE--Műszaki KarThis article discusses how drones are transforming various industries, such as agriculture and surveillance, yet they still face difficulties in autonomously navigating complex environments. To address this, the article introduces a method that combines artificial intelligence (AI) with drone systems to enhance their ability to avoid obstacles. The approach involves the use of deep reinforcement learning (DRL) techniques to better the navigation skills of drones. The authors detail their integrated hardware and software strategy, emphasizing their preliminary findings and the obstacles they encountered. The primary aim of this research is to further the use of autonomous drones in real-life situations.Tétel Korlátozottan hozzáférhető Assessing Radar Performance in Automotive IndustryKhan, Fardeen Ahmed; Istvan, Balajti; DE--Műszaki KarThe research is focused on developing phased array antennas and automotive radars operating on different frequencies and simulating them in various weather conditions to compare their performance.Tétel Korlátozottan hozzáférhető Automobile Radar Sensing with AI-Enhanced Collision AvoidanceFarhat, Georges; Balajti, Istvan; DE--Műszaki KarIn enhancing driving safety, this investigation employs a combination of artificial intelligence (AI) and advanced radar systems to proactively predict and prevent collisions, thereby elevating overall vehicle safety. The study delves into the pivotal role played by radar-based systems in preempting crashes, highlighting key concepts that advocate for the collaborative use of AI and radar to bolster road safety, drawing insights from pertinent literature. Going beyond theoretical considerations, the research takes an empirical approach, conducting a thorough risk evaluation, identifying potential obstacles, and formulating safety protocols. Utilizing carefully designed measurement setups for processing radar signals, the study aims to facilitate effective braking and smooth cruising, outlining four crucial measurement steps and techniques for data interpretation and evaluation. Through systematic operation and testing initiatives, the research critically examines the effectiveness of collision prevention through simulations and theoretical foundations. Furthermore, the paper explores future directions by investigating how the integration of technology into smart transportation systems could further enhance road safety. This endeavor represents a significant stride in advancing vehicle safety by integrating AI and radar technologies. The research aspires to cultivate an environment where individuals feel safer whether driving personal vehicles or utilizing public transit. Through the provision of proactive collision avoidance services and competence development programs, the goal is to foster an atmosphere conducive to safety for all individuals involved.Tétel Korlátozottan hozzáférhető Automotive Radar Array Antennas Enhancing Car Safety and AutonomyKuteich, Alaan; Balajti, Istvan; DE--Műszaki KarThis thesis explores sensor fusion techniques and hardware solutions to advance self-driving cars. It provides a historical overview, conducts a literature review, and analyzes various sensors (cameras, LiDAR, radar, IMUs) in terms of cost and performance. The research introduces advanced sensor fusion algorithms and cost-effective hardware solutions to seamlessly integrate data from different sensors, addressing challenges in existing systems. Real-world testing and simulations validate the proposed system's effectiveness under diverse driving conditions, contributing valuable insights to the autonomous vehicle industry and paving the way for further advancements in self-driving technology.Tétel Korlátozottan hozzáférhető COMPARISON OF SIMPLIFIED AND COMPLEX MODELS OF A THREE-PHASE PERMANENT MAGNET BRUSHLESS DIRECT CURRENT MOTOR IN ELECTRIC VEHICLESGhareeb, Abdullah Waheeb Jaffer Omer; Babangida, Aminu; DE--Műszaki KarOne of the most viable options presented for eliminating environmental concerns while keeping energy efficiency in the field of mobility and transportation, is electrical vehicles (EV). The overall performance of the electrical vehicles can be determined by their electric motors. The utilization of the permanent magnet brushless direct current (PMBLDC) motors as an applicable selection for the electrification of the vehicles. In this research, a deep examination and performance evaluation of the use of PMBLDC motors in electric vehicles, in precise a comparison of a simplified and complex models of a three-phase, 4-pole Y-connected PMBLDC motor was performed. Performance evaluation and enhancement and assessment of behavior under ambient temperatures and various controlling algorithms, was done by creating the models using MATLAB/Simulink environment. The research resulted in optimizing the overall performance of the motor as well as the full electric powertrain.Tétel Korlátozottan hozzáférhető Control and data processing of creep test machineMadbak, Hanna; Almusawi, Husam; DE--Műszaki KarThe Department of Mechanical Engineering was assigned an industrial project that involves measuring the deformation of pipelines over a period of 42 days under constant stress. In response to this requirement,a creep test machine was designed and constructed. However, given the need to take multiple measurements at specific intervals, it is challenging for an individual to be present throughout the entire duration. Therefore, Automating the entire process was the ideal solution.Tétel Korlátozottan hozzáférhető Controlling Festo MPS Station With Beckhoff Industrial ControllerKuray, Ahmet Utku; Keczán, László; DE--Műszaki KarThis thesis is about controlling a Festo Modular Production System (Festo MPS) station with Beckhoff industrial controller, a Beckhoff Programmable Logic Controller (PLC). This thesis aims to create a simulation of industrial automation environment with Festo MPS station, by controlling this station to sort workpieces by using sensors and actuators according to the colour and the type of material of the workpieces.Tétel Korlátozottan hozzáférhető DESIGN AND DEVELOPMENT OF MAZE-SOLVING ROBOTALAKLOOK, ABDALKAREEM; ALMUSAWI, HUSAM ABDULKAREEM; DE--Műszaki KarThe principal aim of this project is to develop a sophisticated mobile robot that can navigate mazes on its own. The robot's unique quality is the way it uses state-of-the-art technologies, including a variety of sensors that improve its ability to solve mazes. Especially, ultrasonic sensors provide for accurate obstacle detection, which helps with obstacle avoidance when navigating a maze. In addition, two infrared sensors improve ambient awareness and three-line tracking sensors guarantee accurate path following. The robot gains a new level of use with the integration of Bluetooth technology. This function makes the robot easy to operate with a cell phone, making it accessible and easy to use even for people who are not very techsavvy. The robot demonstrates its versatility by completing wall and line mazes, among other maze configurations. The robot's remarkable capacity to interpret and carry out user-drawn maps stands out. Customers can draw a map on their phone, and the robot will follow it on its own. The robot's usefulness is greatly increased by this feature, which makes it perfect for interactive presentations and learning situations.Tétel Korlátozottan hozzáférhető Development of an optimal energy management strategy for a Jetta MK5 hybrid vehicleSilavinia, Alaa; Almusawi, Husam; Aminu , Babangida; DE--Műszaki KarThis thesis employs MATLAB/Simulink/Simscape for a simulation analysis, aiming to determine the optimal fuel efficiency for parallel hybrid electric vehicles. The simulation model integrates theoretical frameworks and actual data to precisely assess hybrid powertrain performance across diverse driving conditions. Model accuracy is verified by comparing simulation results with experimental data. The thesis shows the impact of key parameters such as battery capacity, electric motor power, engine specifications, vehicle body, and driving cycles on hybrid electric vehicle fuel economy. The findings suggest that parallel hybrid electric vehicles can achieve notably high fuel efficiency. The thesis proposes a dynamic method for developing the powertrain of parallel-hybrid cars, incorporating real-world measurements and a genetic algorithm to optimize Proportional Integral Derivative parameters for synchronous motor regulation.Tétel Korlátozottan hozzáférhető Development of Face Following RobotZhang, Zheyuan; Almusawi , Husam Abdulkareem; DE--Műszaki KarThis face following robot project realises real time following of faces and human bodies by the robot in different environments through the integrated application of HOG (Histogram of Oriented Gradients) algorithms, video processing, servo control and sensor technologies. The project first establishes a clear workflow, including the steps of video head startup, image processing, servo control, and distance sensing. Through different and multiple experiments, the parameters of the HOG algorithm were adjusted, including the tolerance value, cell size and block size, these data improved the accuracy of detecting human targets and also improved the accuracy of the robot's work. Although the project achieved satisfactory results, there is still have some improvement. It is recommended to optimise the algorithms to make real time detection efficiency , and also increase flexibility of the robot in different surroundings, and to consider the introduction of more advanced hardware and machine learning techniques to improve system performance. Overall, the project provides useful experience in applying the HOG algorithm to real face following robot projects, and also suggests potential directions for future improvements.Tétel Korlátozottan hozzáférhető Development Of IOT Based Interface For Drone Systems To Improve HealthacareMohamed, Ahmed; Mikuska, Robert; DE--Műszaki KarThe thesis aims to optimize the emergency services in health departments, by integrating drones into them and creating an IOT-based interface to control and monitor these drones. A simulation environment, ground control station, flight controller, and ROS have been utilized to create the drone system core, where ROS acts as the middleware that connects all of the software and hardware components using a set of tools and libraries. The drone is autonomous and should be able to execute the mission of delivering medical supplies based on given coordinates only. A path generation and following system has been created, and an object detection system will be a future system that will be working in coordination with the path following and generation system. A user interface has been created and connected to the system.Tétel Korlátozottan hozzáférhető Development of the extended Kalman Filter for Robotic NavigationAmeh, Eineje; Almusawi, Husam; DE--Műszaki KarThis paper explores advances in autonomous navigation, emphasizing its crucial role in self-driving vehicles, unmanned aerial vehicles, and spacecraft. The focus is on leveraging the Extended Kalman Filter (EKF) to enhance precision and reliability in non-linear dynamic systems. The EKF, an extension of the Kalman Filter, addresses real-world non-linearities by integrating linearization, enabling accurate state estimates. The study underscores the EKF's effectiveness through in-depth scenario analyses, showcasing its contribution to improved navigation accuracy. By applying the recursive EKF algorithm, which incorporates noisy sensor measurements and system dynamics, the research aims to elevate the reliability and precision of state estimation in dynamic systems. Notably, the study highlights the importance of linearizing equations for accurate state estimation in complex and dynamic environmentsTétel Korlátozottan hozzáférhető EMG SIGNALS BASED GESTURE RECOGNITION FOR COMPUTER INTERFACEDhaiban, Magd Saeed Dagham Mohammed; Almusawi , Husam Abdulkareem; DE--Műszaki KarThis paper presents an electromyogram (EMG) signals based hand gesture recognition for computer interface using an inside of the forearms-placed dual channel EMG sensor (shimmer 3). EMG signals were gathered from 10 participating subjects after filtration and normalization and to improve the data set used to train the machine -learning model, the system uses Time-Domain (TD) features and Frequency-Domain (FD) features of the signals that were collected. To develop a classification model of the signals produced by four different gestures performed with two hands, classification learner app in MATLAB was used along with an Ensemble Boosted Trees learning model with the chosen features, the Bayesian optimizer was then used and result with an accuracy of 84.1%. An RC car was used as a sample application so that it could be operated by the user's hands EMG signals rather than a remote control device.Tétel Korlátozottan hozzáférhető Energy Harvesting Mechanisms for Mobile RobotsTurgambayev, Daulet; Husam, Almusawi; DE--Műszaki KarThis paper explores energy harvesting methods, including solar and vibrational energy, for autonomous agricultural robots. It talks about the effectiveness of solar harvesting based on the time of day and the weather. The use of piezoelectric materials and sensors for vibrational energy harvesting is described in depth, with solar energy harvesting. The study emphasizes the significance of task optimization, navigation, energy management, and environmental adaptation. Key factors are durability, upkeep, and remote monitoring. This research advances the creation of autonomous robots that can improve sustainability and agriculture operations by addressing these issues.Tétel Korlátozottan hozzáférhető enhacing mailbox functionality through automation and fingerprint aunthenticationLinganwa, Bouhari Minega; Aminu, Babangida; DE--Műszaki KarThis thesis aims to design a smart mailbox system that makes use of cutting-edge technology to detect the arrival of mail, inform users, and ensure secure access of the retrieval mail.Tétel Korlátozottan hozzáférhető Improvement of Safety Sensors in Autonomous VehiclesDina, Sadia Kabir; Balajti, Istvan; DE--Műszaki KarThe focus of this research is to focus on the framework for sensor fusion, which allows for selective fusion of sensor inputs in a context aware way. In the case of object detection performed with a challenging factual data base, this will be verified by theoretically, qualitatively and quantitatively analysis. Here we will discuss ways of improving the current fusion architecture. This study would thoroughly examine the purpose, characteristics, benefits and disadvantages of sensors deployed in autonomous vehicles. To assess their effectiveness, benefits and disadvantages, an examination will be carried out on specific types of sensors. In addition, in view of the current software and hardware situation, it would be important to concentrate on clarifying the volatility nature of risk factors which could jeopardize the reliability and efficiency of these sensors. In examining risk assessment methodologies, the importance of a comprehensive and dynamic risk assessment would be emphasized. The intrinsic limits of present sensor technology will be thoroughly discussed by generic concerns, such as restrictions in sensor resolution and range. The need for an active strategy of adapting sensor systems to the continuously evolving environment is highlighted by dynamic risks. This research will also explore some of these risks, e.g. rapid changes in transport infrastructure, new cybersecurity attacks and changing legal requirements. The goal of this study is achieving a seamless integration of autonomous car sensors into our transportation scene requires finding a balance between the cognitive abilities of human drivers and their technical capabilities. A major feature of this study will be to evaluate the way auto sensors are able to make decisions such as human drivers. Human drivers are intuitive decision makers, flexible in unexpected situations and emotionally intelligent compared to autonomous car sensors that focus on accuracy, coherence or real time processing of large amounts of data. In principle, the study would offer a comprehensive investigation of autonomous vehicle sensors and acknowledge complex relationships between risks variables, software, hardware or decision-making processes. In this study, a brief discussion will be made of the future scope for implementing the findings of the research.Tétel Korlátozottan hozzáférhető KINEMATIC ANALYSIS OF A 4 DEGREES OF FREEDOM SCARA ROBOT AEM FOCUSING ON THE FORWARD AND INVERSE KINEMATICS USING MATLABAl-jaberi, Abdullah Khaled Abdullah; Korsoveczki , Gyula; DE--Műszaki KarThis project presented Kinematic analysis of a SCARA robotic system with four degrees of freedom focusing on kinematics part of mechanism and get its forward and inverse by using MATLAB. SCARA robotic is a type of industrial robot stands for “Selective Compliance Articulated Robot Arm”, it has a hight speed and hight accuracy for this reason it’s used for many applications that’s require a high precision assembly, pick-and-place tasks, and other applications in manufacturing. its arm has four degrees of freedom, the type of its joints is RRPR, SCARA robots typically have a cylindrical work envelope, meaning they can reach areas within a circular or cylindrical space. This makes them well-suited for applications where the workspace has a relatively consistent shape. We control it forward and inverse kinematics motion by utilizing different joint variables.Tétel Korlátozottan hozzáférhető license plate recognition systemSmagulov, Arlen; Alowmari, Ahmed; DE--Műszaki KarThis thesis focuses on the development and deployment of a sophisticated licence plate recognition (LPR) system, utilising machine learning and computer vision methodologies, specifically targeting residential regions. The main aim of this study is to develop a resilient system that can effectively detect and categorise licence plates in real-time from both pictures and video feeds. This system will be optimised to enhance access control within residential complexes. The objective of this study is to overcome the current deficiencies observed in residential-focused Licence Plate Recognition systems. The aforementioned restrictions pertain to difficulties associated with achieving accuracy, adjusting to diverse environmental circumstances, and the requirement for uninterrupted, instantaneous data processing. The objective of this thesis is to further the development of licence plate recognition technology, with a specific focus on addressing the challenges posed by residential contexts.