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Utilizing Data Analytics On Single-Phase Ac Arc Flash Testing And Model Development, Po-Chen Chen

Electrical Engineering Dissertations - Archive

Arc flash events could result in injuries, fatalities, and lead to severe medical expenses, equipment replacement cost, and even litigation, fines, and loss of business. Such events could also tremendously traumatize the personnel psychosocially and neurologically. Therefore, it is critical to accurately understand the potential arc flash hazards from all the real applications. Yet, due to the random complex nature of arc flash events and great number of uncertain variables involved, there are challenges to provide mathematical models for equipment designers in determining the arc-flash fault current and the incident energy of various types of events. The early arc flash …

A Partial Discharge Inception Voltage Modeling Approach, Shilpi Mukherjee, Tristan Mark Evans, David Huitink, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

A partial discharge inception voltage modeling approach promoting design-for-reliability considerations in advanced power modules is presented. As power modules are being operated at higher voltages and become more compact to meet power density demands, there is an increased risk of partial discharge, the silent precursor to electrical breakdown that degrades insulation material. The trade-off between voltage class and module compaction must be quantified. This work presents a methodology to model the tradeoff for any substrate and encapsulant material. A surface charge density-based partial discharge inception voltage (PDIV) model was developed to overcome the challenges in electric field-based models. The model …

High-Efficieny Ultrafast Mid-Infrared Source For Strong Field Science, Fangjie Zhou

Electronic Theses and Dissertations, 2020-2023

The potential of high-energy sources within the mid-infrared region (3-8 μm) has garnered significant attention for diverse research and industrial applications. Millijoule pulses extending beyond 3 μm can facilitate the production of x-rays with photon energies in the keV range through high harmonic generation (HHG). These high-energy x-ray pulses enable the characterization of electron dynamics within molecules and condensed matter materials. Additionally, the atmospheric transmission window between 3-5 μm allows lasers within this spectral range to deliver energy efficiently to distant targets via optical filaments without divergence, highlighting promising prospects for defense applications. In contrast to laser amplifiers, which are …

Optical Design Study Of A High-Resolution Spectrograph Utilizing Photonic Lanterns For A Large Fiber Array Telescope, Richard D'Alo

Graduate Thesis and Dissertation 2023-2024

Large area fiber array telescopes are a relatively modern development in the long history of telescope design and effectively create a single large equivalent aperture by combining many smaller unit telescopes at a fraction of the cost. In this study a spectrograph optical design is demonstrated that utilizes photonic lanterns in the input fiber feed for the Large Fiber Array Spectroscopic Telescope (LFAST) design concept, where photonic lanterns provide a simplified approach to the fiber feed originally proposed for LFAST. Conservation of etendue is applied to derive the relationship between slit size and photonic lantern ratio, and classical echelle spectrograph …

Improvement Of The Break And Steering System For The Golf-Cart, Rami Raed Mustafa

Senior Honors Theses and Projects

This project aims to gain knowledge and test theories related to autonomous vehicles using an electric golf cart as a test platform. There are several goals set, including obtaining electrical and controls experience related to autonomous driving and expanding their electrical engineering skills. The project has the potential to benefit the general population, as the electric golf cart shares similar attributes to a motor vehicle. Through diligent work and research, three key objectives have been achieved: transforming the previous single Arduino system into two mega Arduinos, reconfiguring the placement of the steering motor, and implementing an emergency braking system. Improving …

Design And Development Of Industrial Internet Of Things For Multi-Cloud Factory Vehicle Monitoring System, Patchapong Kulthumrongkul

Chulalongkorn University Theses and Dissertations (Chula ETD)

Material handling equipment, such as forklifts, is broadly used in many industries to increase production efficiency. However, if the equipment unexpectedly breaks down, it can potentially interrupt manufacturing. It's beneficial for the industry to monitor equipment usage data in real-time so that engineers can identify faults before they occur. In this thesis, a prototype for a factory vehicle monitoring system has been designed and implemented. The proposed solution is to acquire real-time usage data from the motor drive of the factory vehicle and send the data to the cloud via narrowband IoT. The received real-time data streams can be stored …

Small Objects Detection In Aerial Imagery For System-On-Chip Fpgas, Wimonthip Saenprasert

Chulalongkorn University Theses and Dissertations (Chula ETD)

Unmanned aerial vehicles (UAVs) offer significant advantages in accessing remote or high-risk locations. Yet, they also present challenges concerning privacy and safety. Effective air traffic management is crucial for ensuring compliance with security regulations. The primary objective is to monitor the flight trajectories of target objects in the airspace, necessitating efficient object detection, especially for distant objects, to facilitate surveillance and preparedness for addressing potential threats. However, the current performance of existing models in detecting small objects is inadequate for real-time surveillance applications. This study advocates prioritizing object detection over precise prediction of object bounding box sizes. We propose a …

Constructing Series, Parallel And Mixed Circuits With Lightbulbs And Analyzing Their Behaviors, Adaeze A. Eze

A with Honors Projects

This honors project was an experiment "to find out if the principles of a series, parallel and a mixed circuit still apply under the given condition (varying bulb resistance)."

Evaluating The Impact Of Increased Cycling On Thermal Power Plants Due To Wind Energy Penetration In The Midwest: A Case Study, Joscelyne Larson

Electronic Theses and Dissertations

One of the most significant shifts in the mix of U.S. electricity generation over the past few years has been the rapid expansion of renewable energy resources, especially solar and wind. However, fossil fuels are still necessary to fulfill the world’s energy requirements. Despite efforts to increase the use of renewable energy sources, these sources can be at times unreliable, causing countries around the world to continue to rely on base load units such as coal and natural gas. This decrease in fossil fuels and increase in renewable energy sources presents many complex issues in terms of power system planning, …

Optimizing Battery Performance: Investigating The Long-Term Impacts Of Bidirectional Battery Management Systems On Battery Cells, Drue Nathaniel Haskins

Graduate Research Theses & Dissertations

With the increased use of batteries in everyday life, it is crucial to have a robust and reliable battery system that can continue to power our devices. This paper will investigate the reliability, impact on the batteries, and functionality of the bidirectional battery management system (BMS). The design uses two bidirectional switches for each cell, one in series with the cell and one in parallel with the other bidirectional switch and cell. This will allow the cell to be taken in and out of the circuit for any reason determined by the BMS. Taking the battery in and out of …

Evaluation Of Low-Cost Radiometer For Surface Reflectance Re-Trieval And Orbital Sensor’S Validation, Dinithi Siriwardana Pathiranage

Electronic Theses and Dissertations

This paper evaluates the Arable Mark 2 sensor, an automated and low-cost radiometer, for its potential to retrieve surface reflectance data and validate orbital sensors such as the Landsat-8 (L8) Operational Land Imager (OLI) Level 2 product. While orbital sensors are widely used for monitoring solar radiation changes, managing natural resources, and understanding climatic trends, atmospheric effects can make it challenging to obtain accurate measurements. Equipped with multiple sensors, including long-wave and short-wave radiometers, the Arable Mark 2 sensor can measure upwelling and downwelling irradiance to calculate surface reflectance. To assess the accuracy and consistency of the Arable Mark 2 …

Extended Cross-Referenced Analysis Using Data From The Landsat 8 And 9 Underfly Event, Garrison Gross

Electronic Theses and Dissertations

The Landsat 8 and 9 Underfly Event occurred in November 2021, where Landsat 9 flew beneath Landsat 8 in the final stages before settling in its final orbiting path. An analysis was performed on the images taken during this event, which resulted in a cross-referenced with uncertainties estimated to be less than 0.5%. This level of precision was due in part to the near-identical sensors aboard each instrument as well as the underfly event itself, which allowed the sensors to take nearly the exact same image at nearly the exact same time. This initial calibration was applied before the end …

The Development Of Dark Hyperspectral Absolute Calibration Model Using Extended Pseudo Invariant Calibration Sites At A Global Scale: Dark Epics-Global, Padam Bahadur Karki

Electronic Theses and Dissertations

This research aimed to develop a novel dark hyperspectral absolute calibration (DAHAC) model using stable dark targets of "Global Cluster - 36" (GC-36), one of the clusters from "300 Class Global Classification." The stable dark sites were identified from GC-36 called "Dark EPICS-Global" covering the surface types viz; dark rock, volcanic area, and dark sand. The Dark EPICS-Global shows a temporal variation of 0.02 unit reflectance. This work uses the Landsat-8 (L8) Operational Land Imager (OLI) , Sentinel-2A (S2A) Multispectral Instrument (MSI) , and Earth Observing One (EO-1) Hyperion data for the DAHAC model development, where well-calibrated L8 and S2A …

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …

A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …

Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The most common type of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of pancreatic cancers. The five-year survival rate for PDAC due to late diagnosis is 9%. Early diagnosed PDAC patients survive longer than patients diagnosed at a more advanced stage. Biomarkers can play an essential role in the early detection of PDAC to assist the health professional. Machine learning and deep learning methods are used with biomarkers obtained in recent studies for diagnostic purposes. In order to increase the survival rates of PDAC patients, early diagnosis of the disease with a noninvasive test …

Basismap: Sequence-Based Similarity Search For Geomagnetic Positioning, Tevfi̇k Kadioğlu, Burcu Erkmen

Turkish Journal of Electrical Engineering and Computer Sciences

Indoor localization has become a popular topic with the development of location-based services (LBS) and indoor navigation systems. Beside these circumstances indoor positioning has been the focus of attention for researchers as the most important component of these applications. Many signals are used as distinguishable features for indoor positioning. RF-based Wi-Fi and BLE systems are the most popular ones and these have been preferred because of their high distinguishable feature. The use of geomagnetism, a natural signal found all over the world, has also been of interest to many researchers. Geomagnetic signals being distorted in the indoor area due to …

Variational Autoencoder-Based Anomaly Detection In Time Series Data For Inventory Record Inaccuracy, Hali̇l Arğun, Sadetti̇n Emre Alpteki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Retail companies monitor inventory stock levels regularly and manage them based on forecasted sales to sustain their market position. Inventory accuracy, defined as the difference between the warehouse stock records and the actual inventory, is critical for preventing stockouts and shortages. The root causes of inventory inaccuracy are the employee or customer theft, product damage or spoilage, and wrong shipments. In this paper, we aim at detecting inaccurate stocks of one of Turkey's largest supermarket chain using the variational autoencoder (VAE), which is an unsupervised learning method. Based on the findings, we showed that VAE is able to model the …

Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …

Ocean Vector Wind Measurement Potential From The Global Precipitation Measurement Mission Using A Combined Active And Passive Algorithm, Alamgir Hossan

Electronic Theses and Dissertations, 2020-2023

Ocean surface vector wind (OVW) is an essential parameter for understanding the physics and dynamics of the ocean-atmosphere system, thereby improving weather forecasting and climate studies. Satellite scatterometers, synthetic aperture radars, and polarimetric microwave radiometers have provided almost global coverage of ocean surface vector wind for the last four decades. Nonetheless, a consistent and uninterrupted long-time data record with the capability of resolving sub-diurnal variability has remained a critical challenge over the years. The Global Precipitation Measurement Mission (GPM) is a satellite mission designed to provide space-based precipitation information on a global scale with complete diurnal sampling. This dissertation presents …

Optimizing Constraint Selection In A Design Verification Environment For Efficient Coverage Closure, Vanessa Cooper

CCAC Theses and Dissertations

No abstract provided.

Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones

Theses and Dissertations--Electrical and Computer Engineering

There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual …

Adversarial Attacks, Coarse Robustness, And Dataless Neural Networks: Novel Techniques For Improved Classification And Combinatorial Optimization, Ismail Alkhouri

Electronic Theses and Dissertations, 2020-2023

Neural networks (NN) have become a central component in most machine learning systems. However, studies have shown that these models are not robust against adversarial attacks. As such, in this dissertation, we explore four directions. In the first direction, we investigate adversarial attacks on two hierarchical classification (HC) models: the Flat HC (FHC), and the Top-Down HC (TDHC). In particular, we formulate attacks against these models by using convex programming. Through experimental results, it is shown that FHCs are more robust than TDHCs. Second, we formalize a new notion of coarse robustness that is defined with respect to a specified …

Generalizable And Adaptable Data-Driven Methods For Overcoming Barriers To Practical Industrial Condition Monitoring, Matthew B. Russell

Theses and Dissertations--Electrical and Computer Engineering

The future of smart manufacturing relies on predictive maintenance systems that intelligently minimize expensive downtime through timely assessment of machine condition. Deep Learning (DL) has achieved excellent performance in industrial condition monitoring experiments, but the constraints of the manufacturing environment prevent many algorithms from being practically deployed on the factory floor. Ubiquitous sensing from online machines generates high velocity data streams that require new techniques for efficient transmission and storage. Despite these ever-increasing data lakes, many applications still lack the data needed for training DL fault diagnosis and wear tracking models since most data is unlabeled and only from nominal …

Unmanned Aircraft Systems For Precision Meteorology: An Analysis Of Gnss Position Measurement Error And Embedded Sensor Development, Karla S. Ladino

Theses and Dissertations--Biosystems and Agricultural Engineering

The overarching objective of this research was to enhance our comprehension of the three-dimensional precision of meteorological measurements obtained using small unmanned aircraft systems (UAS). Two complimentary experiments were conducted to achieve this objective.

The first experiment entailed the development and implementation of a system to determine the global navigation satellite system (GNSS) position accuracy on a UAS platform. This system was utilized to assess the static and dynamic accuracy of L1 and L1/L2 GNSS receivers in real-time kinematic (RTK) and non-RTK fix modes. Adjusted two-sample t-tests revealed significant differences in horizontal and vertical error between RTK and non-RTK receivers …

Investigating The Effects Of Network Dynamics On Quality Of Delivery Prediction And Monitoring For Video Delivery Networks, Obinna C. Izima

Doctoral

Video streaming over the Internet requires an optimized delivery system given the advances in network architecture, for example, Software Defined Networks. Machine Learning (ML) models have been deployed in an attempt to predict the quality of the video streams. Some of these efforts have considered the prediction of Quality of Delivery (QoD) metrics of the video stream in an effort to measure the quality of the video stream from the network perspective. In most cases, these models have either treated the ML algorithms as black-boxes or failed to capture the network dynamics of the associated video streams.

This PhD investigates …

Implementation And Optimization Of Multi-Resonance And Phase Control Of The Electrical Power Take-Off On A Wec Array For Improved Performance, Madelyn G. Veurink

Dissertations, Master's Theses and Master's Reports

Many governments around the world are pledging to reduce their consumption of fossil fuels as they look to curb the amount of green house gasses they release into the atmosphere. These green house gasses are what scientists blame for global warming and the recent increase in extreme weather events. Producing electricity is one of the largest producers of these gasses but utilizing renewable sources can greatly decrease the amount of green house gasses produced. Common forms of renewable energies are wind and solar and both of these green energies have reached a state of maturation where they are economically viable …

Exploration Of Robotics Need In The Medical Field And Robotic Arm Operation Via Glove Control, Aditi Vijayvergia

Master’s Theses

This thesis project is an exercise in getting hands-on experience in redesigning and modifying a robotic system. It also involves understanding the current need for robotic applications in hospital settings. To achieve the above, a thorough literature review of the current state of robotics in a hospital setting was conducted. Moreover, a number of interviews with medical care professionals were completed. Three main themes were obtained from the literature review and five main themes were obtained from the interviews which will be presented in this thesis report. The next phase of the project involved redesigning a system that is composed …

Running Shoe Pedometer, Benjamin Kasper

Williams Honors College, Honors Research Projects

Running shoe pedometer aims to solve the issue of worn out running shoes. It can be difficult to know just how many miles you have run in your shoes and when a new pair is needed. Running in old shoes and worn out shoes is heavily linked to injury. My proposed project is a device that is powered by the compressive forces on the shoes soles that counts the number of steps the wearer takes using a microcontroller. Then, when the shoe reaches milestone that indicate it has been used 75% 90% and 100% of its expected life, it will …