Electrical Engineering

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https://hdl.handle.net/20.500.11888/10121

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    Auto-Batch concrete control system
    (2024) Ameer Salam; Mosab Bani jaber
    The automation of concrete factories plays a pivotal role in augmenting efficiency, productivity, and product quality. This graduation project is oriented towards the development and execution of an integrated automation system aimed at overseeing and managing the operations of a concrete factory. The proposed system will encompass a wide array of concrete production facets, including material handling, batching, mixing, pouring, and curing. It will leverage cutting-edge technologies such as programmable logic controllers (PLCs), industrial sensors, and supervisory control and data acquisition (SCADA) software to ensure real-time monitoring and control of the production process. The project will tackle the challenges associated with integrating diverse components, ensuring data integrity, and implementing robust control algorithms. The successful deployment of the automation system is anticipated to yield substantial enhancements in production efficiency, operational cost reduction, and product quality enhancement, thereby contributing to the overall success of the concrete factory.
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    Portable Power Supply
    (2024) Ahmad Ashour; Sabeeh Ashour; Majde Hammad
    When sometimes people go outside home for a trip or picnic, they may need a 230v AC source, especially when they go to place that doesn’t have any access of traditional electric outlet like forests. So, it wishes to build a device which will provide electrical power and can be portable and easy to transport and compact for everyone who love to go outside for long time. In this project Li-ion batteries are used to provide electric power to the device. Why Li-ion batteries, because these batteries are the most popular and can be recharged and used on most of electric devices like mobile phones because of their reliability, efficiency and long lasting. And by using power electronics an inverter will be built to produce pure 230v sine wave in our device, and it will use different DC output ports to charge a phone or a laptop, and this device will provide built in radio and Bluetooth speaker and it will support wireless charging for some devices and it will provide some helpful camping features.
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    Telecommunication Engineering
    (2024) Eman Alawnah
    The Vehicle Tracking Based on GSM&GPS project brings together innovative approaches combining both GPS &GSM technology to create a vehicle tracking system that is both efficient and practical. Its functioning relies on a smartphone and the Arduino UNO, offering cost-effective usage in numerous industries. By using GPS tech, our Vehicle Tracking System tracks the vehicle's movement—accurately determining longitude and latitude data. This information is then transmitted through the GSM network which uses cellular towers- sending & receiving data in text message form; this includes identifying visualizations of each respective location on a map. Adding an ignition sensor provides a level of security. It sends a text message warning whenever someone tries to steal the vehicle acting as a deterrent, against theft. This aligns with the goal of reducing vehicle theft as it gives users a way to monitor, control and protect their vehicles. The incorporation of a control system, for a DC motor into the framework of an Arduino Uno, GPS GSM module and an ignition sensor signifies an approach to managing vehicles. This system allows users to have control over the DC motor by sending SMS commands. The simplicity and ease of use of this mechanism is demonstrated by instructions like "turn vehicle on" which activates the DC motor. The data is sent in as a text message, which includes the longitude, latitude, and location on the map. The message can be received on a mobile phone or any device capable of receiving text Messages. This project holds particular significance in detecting stolen vehicles, as it enables swift and precise recovery of the vehicle. Overall, Vehicle tracking systems have many applications today and will continue to develop in the future due to the value of the service they provide in terms of tracking vehicles and knowing their location at any time.
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    Enhanced Control Strategy for Single-Phase Grid-Tie Inverter with Repetitive Learning Controller
    (2024) Yahya Naser; Hassan Bargouth
    Photovoltaic (PV) power being supplied to the utility grid is becoming increasingly popular as the world’s power demand continues to rise. Solid-state inverters are the key technology that enables the integration of PV systems into the grid. Inverters are used to convert the DC voltage obtained from the PV system to AC voltage, which is then fed to the grid. Hysteresis control is typically used to control the inverter to regulate the real and reactive power injected from the PV into the grid. However, in this project, the real and reactive power will be controlled using a different technique, namely the PI controller in addition to the repetitive controller. The repetitive controller will compensate for any errors introduced by the PI controller in tracking the sinusoidal reference, as shown in Figure 1. Figure 1: PV multi-level-based Grid The project will first be simulated in MATLAB Simulink. The hardware components include a microcontroller, current, voltage sensors, H-bridge, and transformer to implement both the PI and the repetitive controllers, in addition to generating a PWM signal to the H-bridge to control the injection of real and reactive power into the grid.
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    AIEN Artificial Intelligence Electrical Nose
    (2024) Ameer Abo liel; Malath Ghazal
    nspired by the high drug smuggling crime rates all over the world, and due to the fact that current mechanisms of drug detection in airports cause discomfort to many travelers worldwide, the need for new reformed detection mechanisms is constantly growing. Using trained K9 dogs could cause many fearful scenarios that could cause trauma to innocent patients. The new mechanism we are presenting to you shows instantaneous results about the material detected. This project presents an artificial intelligence electronic nose (AIEN) for detecting and identifying various odors and substances. The AIEN utilizes MQ gas sensors and machine learning algorithms to analyze and classify different volatile organic compounds. A filtration system with ethanol is implemented to ensure accurate results between samples. The device also incorporates DC and AC fans and motors controlled by a microcontroller to automate the sampling process. Extensive testing produced consistent characteristic odor profiles and plots for different substances like perfumes and alcoholic beverages. The fusion of gas sensor technology with artificial intelligence offers an innovative approach to processing complex olfactory data. AIEN provides a proof of concept for the capabilities of intelligent odor detection systems in fields ranging from quality control to law enforcement