Absolute Electrical Impedance Tomography and Spectroscopy (aEITS) is a non-intrusive imaging technique, that reconstructs images based on estimates of the absolute internal impedance distribution of an object. However, without the availability of a reference frame, it suffers from poor image quality when general assumptions are used to form the prior information about the object. This problem is intensified when selecting a multiplexing technique that introduces significant data inconsistencies. Recent attempts to solve this problem are to use data from previous empirical studies that acquired scans from Magnetic Resonance Imaging (MRI). Another approach is to use statistical methods to estimate the boundaries of the expected internal domains of the object. These approaches have shown an improvement in the reconstructed images, but either rely on data from other imaging modalities or continue to use a reference frame taken at an earlier time. Therefore, this is a non-trivial problem. In this thesis, the concept of Orthogonal Chirp Division Multiplexed aEITS (OCDM-aEITS) is introduced as an alternative multiplexing technique. OCDM-aEITS allows the simultaneous application of orthogonal wideband chirp current waveforms at all stimulation electrodes, while measuring the resultant boundary potentials. Given a single wideband measurement frame, a reference set, prior information, and several absolute images can be reconstructed. Consequently, there no longer is a need to acquire reference data, from an earlier time, or prior information from other imaging modalities. Furthermore, OCDM-aEITS overcomes some of the data inconsistencies from other multiplexing techniques (such as the data inconsistencies caused by sequential stimulation or spikes from fast pseudorandom pulse stimulation), while reconstructing images with comparable quality to those in the related literature. The experimental results from this thesis (acquired from the reconstructed images of a phantom test tank containing biological specimen), achieved an average position and size error of 3.88 % and 2.49 %, respectively.

Throughout the years, sensors have been an integral part of automation, alert, and medical systems. Many of these systems measure physiological characteristics of the human body to alert themselves of their current conditions. Drowsy driver systems, for instance, measure the eyes and facial movements with a camera to determine if the driver is falling asleep at the wheel. Electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) employ electrodes on the human body to measure electrical activity of a patient’s REM sleep cycle patterns. Pulse oximeters use optical light through a process called photoplethysmography (PPG) to measure heart rate. As diverse as these all may be, this thesis attempts to prove infrared technology as a single, resourceful, and inexpensive method for implementing all the aforementioned systems. This thesis specifically explores the development of Silicon Laboratories’ Si1143 Infrared Proximity/Ambient Light Sensor into a pair of eye tracking/heart rate detecting glasses. Through the use of a LabVIEW interface, a novel algorithmic solution is also presented to classify the eye movements and detect the heart rate signal. The results from the tests and calculations show that the Si1143 sensor can detect eye movements using only a 52μW of power. The novel algorithm can also classify the blinking motions robustly, but the algorithm starts to fail when additional motions are added. The results also show that the Si1143 sensor can detect heart rate using Reflection PPG method, but imprecise placement of the sensor on the glasses will render the measurement useless. This thesis concludes that Si1143 sensor is sensitive enough to track the human eye and measure the heart rate, but further work is required to make it robust.

The technological advances made in the photovoltaic industry have led to a vast exploration of self-sustaining systems. As the consumer demand for electricity rises from increasing population and development of existing technologies, new practices in system designs are required to relieve the impact on the electrical grid. This thesis delves into a developing concept of using photovoltaic modules for roadway lighting, with emphasis on establishing the fundamental design for a “spot-lighting” luminaire. By effectively extinguishing various sections of the luminaire in the absence of pedestrian trafficking, the proposed design and implementation will minimize the prolonged costs, as well as the overall power consumption. Furthermore, as the first stage in development, this thesis includes justifications for design and part selection, while complying with numerous requirements set forth by the City of Los Angeles and in accordance with regulations established by the Illuminating Engineering Society of North America (IESNA). To accomplish these goals, copious amounts of performance tests and simulations, both before and after system implementation, will characterize the overall feasibility of the stand-alone lighting application.

<p>In the past decades, great advances in biomedical imaging towards using less invasive and more sensitive imaging modalities have enabled early detection of diseases through timely diagnosis of patients. Positron emission tomography (PET) imaging, as one of the recent imaging technologies, provides imaging from cellular-level metabolic changes in tissues. This gives PET imaging a substantial lead in detecting disease in their very early stages. PET imaging provides high sensitivity and chemical specificity. However, it suffers from low resolution compared to other imaging methods. Time of Flight (ToF) PET imaging, one of the derivations of the PET, improves the imaging by exactly determining the position of the annihilation event using a time digital converter (TDC). By achieving the timing information of the incident anti-parallel photons coming from an event in ToF PET scanner, the TDC helps to determine the exact location of the event. So, it increases the resolution of the PET scanner.</p> <p>A ToF PET custom-designed TDC has been proposed in this work. The designed TDC offers relatively high resolution and dynamic range (DR) to satisfy some PET imaging specifications. To increase the sensitivity and reduce the noise and latency, in-pixel design of TDC is desired. Therefore, a time digital converter that is specifically designed for ToF PET should follow a strict set of criteria in its design procedure. A three-staged hierarchical TDC was designed and implemented in 0.13μm standard CMOS technology to reduce the total number of delay elements for this area limitation issue. Also, a novel half-CLK period interpolation idea was proposed to reduce the total size of the TDC even more. A counter and half-CLK counter construct the coarse stage of the TDC. A delay locked loop (DLL) works as the first fine interpolator, while, the Vernier delay line (VDL) acts as the second fine interpolation stage.</p> <p>A high resolution of 39ps was achieved with a relatively high DR of 1.28μs and the measured DNL and INL of 0.2T_LSB and 0.4T_LSB. Due to all area reduction techniques used, the final designed TDC measures for 0.11 mm², which is much smaller than other similar TDCs with the same resolution and DR. As the amount of delay in the delay elements in the TDC are susceptible to any change in the environmental changes, a delay locking method was used to compensate for process, voltage and temperature (PVT) variations. <strong><br /> </strong></p>

The objective of this PhD research is to develop robust, and non-intrusive condition monitoring methods for induction motors fed by closed-loop inverters. The flexible energy forms synthesized by these connected power electronic converters greatly enhance the performance and expand the operating region of induction motors. They also significantly alter the fault behavior of these electric machines and complicate the fault detection and protection. The current state of the art in condition monitoring of power-converter-fed electric machines is underdeveloped as compared to the maturing condition monitoring techniques for grid-connected electric machines. This dissertation first investigates the stator turn-to-turn fault modelling for induction motors (IM) fed by a grid directly. A novel and more meaningful model of the motor itself was developed and a comprehensive study of the closed-loop inverter drives was conducted. A direct torque control (DTC) method was selected for controlling IM’s electromagnetic torque and stator flux-linkage amplitude in industrial applications. Additionally, a new driver based on DTC rules, predictive control theory and fuzzy logic inference system for the IM was developed. This novel controller improves the performance of the torque control on the IM as it reduces most of the disadvantages of the classical and predictive DTC drivers. An analytical investigation of the impacts of the stator inter-turn short-circuit of the machine in the controller and its reaction was performed. This research sets a based knowledge and clear foundations of the events happening inside the IM and internally in the DTC when the machine is damaged by a turn fault in the stator. This dissertation also develops a technique for the health monitoring of the induction machine under stator turn failure. The developed technique was based on the monitoring of the off-diagonal term of the sequence component impedance matrix. Its advantages are that it is independent of the IM parameters, it is immune to the sensors’ errors, it requires a small learning stage, compared with NN, and it is not intrusive, robust and online. The research developed in this dissertation represents a significant advance that can be utilized in fault detection and condition monitoring in industrial applications, transportation electrification as well as the utilization of renewable energy microgrids. To conclude, this PhD research focuses on the development of condition monitoring techniques, modelling, and insightful analyses of a specific type of electric machine system. The fundamental ideas behind the proposed condition monitoring technique, model and analysis are quite universal and appeals to a much wider variety of electric machines connected to power electronic converters or drivers. To sum up, this PhD research has a broad beneficial impact on a wide spectrum of power-converter-fed electric machines and is thus of practical importance.

University of Macau / Faculty of Science and Technology / Department of Electrical and Electronics Engineering

University of Macau / Faculty of Science and Technology / Department of Electrical and Electronics Engineering

As part of the approaches used to meet climate goals set by international environmental agreements, policies are being applied worldwide for promoting the uptake of Electric Vehicles (EV)s. The resulting increase in EV sales and the accompanying expansion in the EV charging infrastructure carry along many challenges, mostly infrastructure-related. A pressing need arises to strengthen the power grid to handle and better manage the electricity demand by this mobile and geo-distributed load. Because the levels of penetration of EVs in the power grid have recently started increasing with the increase in EV sales, the real-time management of en-route EVs, before they connect to the grid, is quite recent and not many research works can be found in the literature covering this topic comprehensively. In this dissertation, advances and novel ideas are developed and presented, seizing the opportunities lying in this mobile load and addressing various challenges that arise in the application of public charging for EVs. A Bilateral Decision Support System (BDSS) is developed here for the management of en-route EVs. The BDSS is a middleware-based MAS that achieves a win-win situation for the EVs and the power grid. In this framework, the two are complementary in a way that the desired benefit of one cannot be achieved without attaining that of the other. A Fuzzy Logic based on-board module is developed for supporting the decision of the EV as to which charging station to charge at. GPU computing is used in the higher-end agents to handle the big amount of data resulting in such a large scale system with mobile and geo-distributed nodes. Cyber security risks that threaten the BDSS are assessed and measures are applied to revoke possible attacks. Furthermore, the Collective Distribution of Mobile Loads (CDML), a service with ancillary potential to the power system, is developed. It comprises a system-level optimization. In this service, the EVs requesting a public charging session are collectively redistributed onto charging stations with the objective of achieving the optimal and secure operation of the power system by reducing active power losses in normal conditions and mitigating line congestions in contingency conditions. The CDML uses the BDSS as an industrially viable tool to achieve the outcomes of the optimization in real time. By participating in this service, the EV is considered as an interacting node in the system-wide communication platform, providing both enhanced self-convenience in terms of access to public chargers, and contribution to the collective effort of providing benefit to the power system under the large scale uptake of EVs. On the EV charger level, several advantages have been reported favoring wireless charging of EVs over wired charging. Given that, new techniques are presented that facilitate the optimization of the magnetic link of wireless EV chargers while considering international EMC standards. The original techniques and developments presented in this dissertation were experimentally verified at the Energy Systems Research Laboratory at FIU.

<p>Accurate characterization of a noisy device starts with an accurate measurement system. Measurement uncertainty and error continues to be a challenging subject as technology advances. The conventional method to noise characterization of on-wafer devices is to determine its noise parameters. To extract the noise parameters of an unpackaged device involves a sophisticated measurement system and calibration procedure. This thesis presents a new automated on-wafer noise measurement system based on Labview 8.5.1 which is used to examine measurement uncertainty for noise parameter extraction. The software program can be used and customized for a wide range of on-wafer noise measurements. This thesis covers the design and operation of the measurement system, which is then used to analyze measurement uncertainty.</p> <p>Measurement uncertainty can be due to various sources from environmental surroundings to instrument settings and the components of the system itself. In many scenarios, inaccuracies are random and cannot be completely resolved. In this thesis, a new tuner characterization technique that improves source tuner characterization is presented. Additionally, a new gain compensation technique is applied to measured noise powers that attempt to improve noise parameter extraction accuracy is proposed. The tuner characterization technique is evaluated against a current industry solution and the affects of the gain compensation technique is evaluated using a newly developed figure of merit. This research work concludes that a direct noise power correction is valid and necessary to further improve noise parameter accuracy. However, the proposed technique when applied resulted in minimal change to the overall noise parameter data. It is found that that source termination selection and total points used for fitting continue to be the major source of uncertainty for noise parameter accuracy.</p> / Master of Applied Science (MASc)

Thesis (M.S. in Electronic Warfare Systems Engineering and M.S. in Electrical Engineering)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Tummala, Murali ; Jenn, David. "September 2009." Description based on title screen as viewed on November 6, 2009. Author(s) subject terms: Cooperative Spectrum Sensing, Source Localization, Multi-Resolution Spectrum Sensing, Three-Bit Hard Combination, RSS-Based Localization, Cognitive Radio, Wireless Sensor Networks, Electronic Warfare. Includes bibliographical references (p. 87-90). Also available in print.