Matching Items (50)
Filtering by
Description
The objective of this paper is to find and describe trends in the fast Fourier transformed accelerometer data that can be used to predict the mechanical failure of large vacuum pumps used in industrial settings, such as providing drinking water. Using three-dimensional plots of the data, this paper suggests how a model can be developed to predict the mechanical failure of vacuum pumps.
ContributorsHalver, Grant (Author) / Taylor, Tom (Thesis director) / Konstantinos, Tsakalis (Committee member) / Fricks, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the Terahertz Imaging system. The GUI was developed in response to a need for synchronization, ease of operation, easy parameter modification, and data management. Along the way, many design decisions were made ranging from choosing a software platform to determining how variables should be passed. These decisions and considerations are discussed in this document. The resulting GUI has measured up to the design criteria and will be able to be used by anyone wishing to use the Terahertz Imaging System for further research in the field of Around the Corner or NLoS Imaging.
ContributorsWood, Jacob Cannon (Author) / Trichopoulos, Georgios (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Analog to Digital Converters (ADCs) are a critical component in modern circuit applications. ADCs are used in virtually every application in which a digital circuit is interacting with data from the real world, ranging from commercial applications to crucial military and aerospace applications, and are especially important when interacting with sensors that observe environmental factors. Due to the critical nature of these converters, as well as the vast range of environments in which they are used, it is important that they accurately sample data regardless of environmental factors. These environmental factors range from input noise and power supply variations to temperature and radiation, and it is important to know how each may affect the accuracy of the resulting data when designing circuits that depend upon the data from these ADCs. These environmental factors are considered hostile environments, as they each generally have a negative effect on the operation of an ADC. This thesis seeks to investigate the effects of several of these hostile environmental variables on the performance of analog to digital converters. Three different analog to digital converters with similar specifications were selected and analyzed under common hostile environments. Data was collected on multiple copies of an ADC and averaged together to analyze the results using multiple characteristics of converter performance. Performance metrics were obtained across a range of frequencies, input noise, input signal offsets, power supply voltages, and temperatures. The obtained results showed a clear decrease in performance farther from a room temperature environment, but the results for several other environmental variables showed either no significant correlation or resulted in inconclusive data.
ContributorsSwanson, Taylor Catherine (Co-author) / Millman, Hershel (Co-author) / Barnaby, Hugh (Thesis director) / Garrity, Douglas (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Commonly, image processing is handled on a CPU that is connected to the image sensor by a wire. In these far-sensor processing architectures, there is energy loss associated with sending data across an interconnect from the sensor to the CPU. In an effort to increase energy efficiency, near-sensor processing architectures have been developed, in which the sensor and processor are stacked directly on top of each other. This reduces energy loss associated with sending data off-sensor. However, processing near the image sensor causes the sensor to heat up. Reports of thermal noise in near-sensor processing architectures motivated us to study how temperature affects image quality on a commercial image sensor and how thermal noise affects computer vision task accuracy. We analyzed image noise across nine different temperatures and three sensor configurations to determine how image noise responds to an increase in temperature. Ultimately, our team used this information, along with transient analysis of a stacked image sensor’s thermal behavior, to advise thermal management strategies that leverage the benefits of near-sensor processing and prevent accuracy loss at problematic temperatures.
ContributorsJones, Britton Steele (Author) / LiKamWa, Robert (Thesis director) / Jayasuriya, Suren (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Alzheimer's disease is the 6th leading cause of death in the United States and vastly affects millions across the world each year. Currently, there are no medications or treatments available to slow or stop the progression of Alzheimer’s Disease. The GENUS therapy out of the Massachusetts Institute of Technology presently shows positive results in slowing the progression of the disease among animal trials. This thesis is a continuation of that study, to develop and build a testing apparatus for human clinical trials. Included is a complete outline into the design, development, testing measures, and instructional aid for the final apparatus.
ContributorsScheller, Rachel D (Author) / Bliss, Daniel (Thesis director) / Corman, Steven (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Speedsolving, the art of solving twisty puzzles like the Rubik's Cube as fast as possible, has recently benefitted from the arrival of smartcubes which have special hardware for tracking the cube's face turns and transmitting them via Bluetooth. However, due to their embedded electronics, existing smartcubes cannot be used in competition, reducing their utility in personal speedcubing practice. This thesis proposes a sound-based design for tracking the face turns of a standard, non-smart speedcube consisting of an audio processing receiver in software and a small physical speaker configured as a transmitter. Special attention has been given to ensuring that installing the transmitter requires only a reversible centercap replacement on the original cube. This allows the cube to benefit from smartcube features during practice, while still maintaining compliance with competition regulations. Within a controlled test environment, the software receiver perfectly detected a variety of transmitted move sequences. Furthermore, all components required for the physical transmitter were demonstrated to fit within the centercap of a Gans 356 speedcube.
ContributorsHale, Joseph (Author) / Heinrichs, Robert (Thesis director) / Li, Baoxin (Committee member) / Barrett, The Honors College (Contributor) / Software Engineering (Contributor) / School of International Letters and Cultures (Contributor)
Created2022-05
Description
The Compact X-ray Light Source is an x-ray source at ASU that allows scientists to study the structures and dynamics of matter on an atomic scale. The radio frequency system that provides the power to accelerate electrons in the Compact X-ray Light Source must operate with a high degree of precision. This thesis measures the precision with which that system performs.
ContributorsBabic, Gregory (Author) / Graves, William (Thesis director) / Kitchen, Jennifer (Committee member) / Holl, Mark (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / Department of Physics (Contributor)
Created2022-05
Description
In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.
ContributorsBou-Ghazale, Carine (Author) / Lai, Ying-Cheng (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2022-05
Description
Engineering, and more specifically, electrical engineering can be a difficult topic to explain through spoken communication. Along with taking years of education to learn and understand necessary topics, the field is riddled with jargon and items that may take lectures to explain. However, this type of education may not be feasible for a younger or inexperienced audience. Therefore, engineers must find new ways to explain such difficult topics, especially in an attempt to garner interest in children, for example, through art.
ContributorsHedges, Madison (Author) / Aukes, Daniel (Thesis director) / Weeks, Eric (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor) / School of Earth and Space Exploration (Contributor)
Created2023-12
Description
This research explores the potential use of microwave energy to detect various substances in water, with a focus on water quality assessment and pathogen detection applications. There are many non-thermal effects of microwaves on microorganisms and their resonant frequencies could be used to identify and possibly destroy harmful pathogens, such as bacteria and viruses, without heating the water. A wide range of materials, including living organisms like Daphnia and Moina, plants, sand, plastic, and salt, were subjected to microwave measurements to assess their influence on the transmission (S21) measurements. The measurements of the living organisms did not display distinctive resonant frequencies and variations in water volume may be the source of the small measurement differences. Conversely, sand and plastic pellets affected the measurements differently, with their arrangement within the test tube emerging as a significant factor. This study also explores the impact of salinity on measurements, revealing a clear pattern that can be modeled as a series RLC resonator. Although unique resonant frequencies for the tested organisms were not identified, the presented system demonstrates the potential for detecting contaminants based on variations in measurements. Future research may extend this work to include a broader array of organisms and enhance measurement precision.
ContributorsChild, Carson (Author) / Aberle, James (Thesis director) / Blain Christen, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2023-12