Theses (Department of Electrical Engineering and Mechatronics)
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Theses collection of the Faculty of Engineering.
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Megjelenítve 1 - 20 (Összesen 28)
Tétel Korlátozottan hozzáférhető Quantifying Vehicle Kinematics Using Passive RadarKhan, Nauman Ahmed; Istvan, Balajti; DE--Műszaki KarThe research demonstrates a significant advancement in vehicle intelligence and road safety. Utilizing custom-designed code and MATLAB's simulation tools, it successfully achieves precise determination of a vehicle's speed, position, and direction using passive radar, effectively addressing the common issues of noise and unclear images prevalent in standard radar systems. It critiques the limitations of traditional simple radar systems in complex automotive environments and proposes a superior approach utilizing passive radar technology. Unlike conventional radar systems that use active emissions, passive radar leverages existing electromagnetic signals, offering a more covert, energy-efficient, and potentially more reliable detection method.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 Swarm RoboticsElkabat, Samer; Almusawi, Husam; DE--Műszaki KarSwarm robotics, inspired by the collective behavior of insects and animals, provides a model for efficient task completion. This summary represents a robotic approach to the positioning, localization, and communication of the swarm using a combination of infrared radiation, inertial measurement unit (IMU), and ESP-NOW communication protocol. The primary focus is to enable coordinated task performance within the swarm while establishing an accurate and reliable localization system. This methodology uses an emitting leader as the main position reference point.Tétel Korlátozottan hozzáférhető System model of Mitsubishi MELFA RV-2AJ 5 DoF industrial robotic arm for state variable estimation using MATLABKazi, Adnan Altaf; Korsoveczki, Gyula; DE--Műszaki KarThe study aimed to create a precise system model for the Mitsubishi MELFA RV-2AJ 5 DoF industrial robotic arm using CAD and MATLAB. Key state variables such as position and velocity were identified to develop an accurate model capable of controlling the robot's movements. A replica of the robot was created, exported to MATLAB Simulink, and a GUI controller was developed to provide precise control over the robot's joint angles. The robot's behaviour was displayed in Mechanics Explorer Simulink, nd a real-time simulation was developed to validate the accuracy of the model. Despite some discrepancies related to the incremental controller during real-life testing, the model's accuracy was still deemed significant and serves as a crucial stepping stone in the development of advanced robotics systems.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 Swarm Symphony: Unravelling Advanced Behaviours and Decision-Making in Robotic CollectivesHussein, Mohammad Haitham Moh'd Tawfiq; AlMusawi, Husam Abdelkareem; DE--Műszaki KarThis thesis provides a comprehensive exploration of the design, programming, and operational intricacies of a group of 2-Wheeled Swarm robots, with a primary focus on unraveling the nuances of collective intelligence and collaborative behavior in swarm robotics. The hardware component involves the meticulous construction of robots featuring multiple sensors and a sophisticated communication module. In the programming phase, emphasis is placed on crafting intricate algorithms for robot behaviors and establishing robust communication protocols to facilitate seamless coordination. Rigorous experimentation underscores the study's findings, showcasing the robots' exceptional adaptability and agility as they navigate environments and respond intelligently to various stimuli. This research not only contributes significantly to the evolving field of swarm robotics through empirical insights but also sparks new avenues for future exploration and innovation within these complex robotic systems.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 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 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 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 Nonlinear Automotive Vehicle Suspension System Integrated With Enhanced PID ControllerGubio, Sherif; Babangida, Aminu; DE--Műszaki KarThis work presents a comprehensive study on a Nonlinear Quarterly Car Passive Suspension System (PSS), designed to address the dynamic challenges encountered in modern vehicles. This novel method combines sophisticated control algorithms with nonlinear elements to enhance the performance of the vehicle. The flexibility of the system to adjust to changing driving preferences and road circumstances is highlighted while delving into the design's essential elements. In order to monitor and alter suspension characteristics in real-time and provide the best ride comfort and vehicle stability.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 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 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 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 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 MrFouad, George; Alowmari, Ahmed; DE--Műszaki Karsmart door access system using RFID, Keypad and GSM moduleTétel 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 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 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.