ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- All Subjects: engineering
- Creators: Holbert, Keith E.
clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated
number of patients living with Parkinson's disease around the world is seven
to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor
signs of Parkinson's disease patients. It is an advanced surgical technique that is used
when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.
This work proposes a behavior recognition model for patients with Parkinson's
disease. In particular, an adaptive learning method is proposed to classify behavioral
tasks of Parkinson's disease patients using local field potential and electrocorticography
signals that are collected during DBS implantation surgeries. Unique patterns
exhibited between these signals in a matched feature space would lead to distinction
between motor and language behavioral tasks. Unique features are first extracted
from deep brain signals in the time-frequency space using the matching pursuit decomposition
algorithm. The Dirichlet process Gaussian mixture model uses the extracted
features to cluster the different behavioral signal patterns, without training or
any prior information. The performance of the method is then compared with other
machine learning methods and the advantages of each method is discussed under
different conditions.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.
This work will review the methods by which power ratings, or ampacity, for underground cables are determined and then evaluate those ratings by making comparison with measured data taken from an underground 69 kV cable, which is part of the Salt River Project (SRP) power subtransmission system. The process of acquiring, installing, and commissioning the temperature monitoring system is covered in detail as well. The collected data are also used to evaluate typical assumptions made when determining underground cable ratings such as cable hot-spot location and ambient temperatures.
Analysis results show that the commonly made assumption that the deepest portion of an underground power cable installation will be the hot-spot location does not always hold true. It is shown that distributed cable temperature measurements can be used to locate the proper line segment to be used for cable ampacity calculations.
This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.
First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.
Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.
The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.
Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.
The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.