Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 105
Description
The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters from human auditory models, such as auditory patterns and loudness, involves computationally intensive operations which can strain device resources. Hence, strategies for implementing computationally efficient human auditory models for loudness estimation have been studied in this thesis. Existing algorithms for reducing computations in auditory pattern and loudness estimation have been examined and improved algorithms have been proposed to overcome limitations of these methods. In addition, real-time applications such as perceptual loudness estimation and loudness equalization using auditory models have also been implemented. A software implementation of loudness estimation on iOS devices is also reported in this thesis. In addition to the loudness estimation algorithms and software, in this thesis project we also created new illustrations of speech and audio processing concepts for research and education. As a result, a new suite of speech/audio DSP functions was developed and integrated as part of the award-winning educational iOS App 'iJDSP." These functions are described in detail in this thesis. Several enhancements in the architecture of the application have also been introduced for providing the supporting framework for speech/audio processing. Frame-by-frame processing and visualization functionalities have been developed to facilitate speech/audio processing. In addition, facilities for easy sound recording, processing and audio rendering have also been developed to provide students, practitioners and researchers with an enriched DSP simulation tool. Simulations and assessments have been also developed for use in classes and training of practitioners and students.
ContributorsKalyanasundaram, Girish (Author) / Spanias, Andreas S (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2013
Description
Today, the electric power system faces new challenges from rapid developing technology and the growing concern about environmental problems. The future of the power system under these new challenges needs to be planned and studied. However, due to the high degree of computational complexity of the optimization problem, conducting a system planning study which takes into account the market structure and environmental constraints on a large-scale power system is computationally taxing. To improve the execution time of large system simulations, such as the system planning study, two possible strategies are proposed in this thesis. The first one is to implement a relative new factorization method, known as the multifrontal method, to speed up the solution of the sparse linear matrix equations within the large system simulations. The performance of the multifrontal method implemented by UMFAPACK is compared with traditional LU factorization on a wide range of power-system matrices. The results show that the multifrontal method is superior to traditional LU factorization on relatively denser matrices found in other specialty areas, but has poor performance on the more sparse matrices that occur in power-system applications. This result suggests that multifrontal methods may not be an effective way to improve execution time for large system simulation and power system engineers should evaluate the performance of the multifrontal method before applying it to their applications. The second strategy is to develop a small dc equivalent of the large-scale network with satisfactory accuracy for the large-scale system simulations. In this thesis, a modified Ward equivalent is generated for a large-scale power system, such as the full Electric Reliability Council of Texas (ERCOT) system. In this equivalent, all the generators in the full model are retained integrally. The accuracy of the modified Ward equivalent is validated and the equivalent is used to conduct the optimal generation investment planning study. By using the dc equivalent, the execution time for optimal generation investment planning is greatly reduced. Different scenarios are modeled to study the impact of fuel prices, environmental constraints and incentives for renewable energy on future investment and retirement in generation.
ContributorsLi, Nan (Author) / Tylavsky, Daniel J (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
Description
A distributed-parameter model is developed for a pressurized water reactor (PWR) in order to analyze the frequency behavior of the nuclear reactor. The model is built based upon the partial differential equations describing heat transfer and fluid flow in the reactor core. As a comparison, a multi-lump reactor core model with five fuel lumps and ten coolant lumps using Mann's model is employed. The derivations of the different transfer functions in both models are also presented with emphasis on the distributed parameter. In order to contrast the two models, Bode plots of the transfer functions are generated using data from the Palo Verde Nuclear Generating Station. Further, a detailed contradistinction between these two models is presented. From the comparison, the features of both models are presented. The distributed parameter model has the ability to offer an accurate transfer function at any location throughout the reactor core. In contrast, the multi-lump parameter model can only provide the average value in a given region (lump). Also, in the distributed parameter model only the feedback according to the specific location under study is incorporated into the transfer function; whereas the transfer functions derived from the multi-lump model contain the average feedback effects happening all over the reactor core.
ContributorsZhang, Taipeng (Author) / Holbert, Keith E. (Thesis advisor) / Vittal, Vijay (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2012
Description
Insulation aging monitoring is widely used to evaluate the operating condition of power equipment. One important monitoring method is detecting partial discharges (PD). PD is a localized breakdown of dielectric and its characteristics can give information about the insulation aging. Most existing test methods cannot identify different kinds of defects. Also, the practical application of PD detection in most existing test methods is restricted by weak PD signals and strong electric field disturbance from surroundings. In order to monitor aging situation in detail, types of PDs are important features to take into account. To classify different types of PDs, pulse sequence analysis (PSA) method is advocated to analyze PDs in the rod-plane model. This method can reflect cumulative effects of PDs, which are always ignored when only measuring PD value. It also shows uniform characteristics when different kinds of detecting system are utilized. Moreover, it does not need calibration. Analysis results from PSA show highly consistent distribution patterns for the same type of PDs and significant differences in the distribution patterns among types of PDs. Furthermore, a new method to detect PD signals using fiber bragg grating (FBG) based PD sensor is studied in this research. By using a piezoelectric ceramic transducer (PZT), small PD signals can be converted to pressure signal and then converted to an optical wavelength signal with FBG. The optical signal is isolated from the electric field; therefore its attenuation and anti-jamming performance will be better than traditional methods. Two sensors, one with resonant frequency of 42.7 kHz and the other 300 kHz, were used to explore the performance of this testing system. However, there were issues with the sensitivity of the sensors of these devices and the results have been communicated with the company. These devices could not give the results at the same level of accuracy as the conventional methods.
ContributorsCui, Longfei (Author) / Gorur, Ravi (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document.
ContributorsMurugesan, Veerakumar (Author) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits that are easily identified or tracked. Indeed it has been shown that patients with enduring symptoms have difficulty describing their problems; therefore, there is an urgent need for a sensitive measure of brain activity that corresponds with higher order cognitive processing. The development of a neurophysiological metric that maps to clinical resolution would inform decisions about diagnosis and prognosis, including the need for clinical intervention to address cognitive deficits. The literature suggests the need for assessment of concussion under cognitively demanding tasks. Here, a joint behavioral- high-density electroencephalography (EEG) paradigm was employed. This allows for the examination of cortical activity patterns during speech comprehension at various levels of degradation in a sentence verification task, imposing the need for higher-order cognitive processes. Eight participants with concussion listened to true-false sentences produced with either moderately to highly intelligible noise-vocoders. Behavioral data were simultaneously collected. The analysis of cortical activation patterns included 1) the examination of event-related potentials, including latency and source localization, and 2) measures of frequency spectra and associated power. Individual performance patterns were assessed during acute injury and a return visit several months following injury. Results demonstrate a combination of task-related electrophysiology measures correspond to changes in task performance during the course of recovery. Further, a discriminant function analysis suggests EEG measures are more sensitive than behavioral measures in distinguishing between individuals with concussion and healthy controls at both injury and recovery, suggesting the robustness of neurophysiological measures during a cognitively demanding task to both injury and persisting pathophysiology.
ContributorsUtianski, Rene (Author) / Liss, Julie M (Thesis advisor) / Berisha, Visar (Committee member) / Caviness, John N (Committee member) / Dorman, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the increased penetration of solar PV, it has become considerable for the system planners and operators to recognize the impact of PV plant on the power system stability and reliable operation of grid. This enforced the development of adequate PV system models for grid planning and interconnection studies. Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force has developed generator/converter, electrical controller and plant controller modules to represent positive sequence solar PV plant model for grid interconnection studies. This work performs the validation of these PV plant models against the field measured data. Sheer purpose of this validation effort is to authenticate model accuracy and their capability to represent dynamics of a solar PV plant. Both steady state and dynamic models of PV plant are discussed in this work. An algorithm to fine tune and determine the electrical controller and plant controller module gains is developed. Controller gains as obtained from proposed algorithm is used in PV plant dynamic simulation model. Model is simulated for a capacitor bank switching event and simulated plant response is then compared with field measured data. Validation results demonstrate that, the proposed algorithm is performing well to determine controller gains within the region of interest. Also, it concluded that developed PV plant models are adequate enough to capture PV plant dynamics.
ContributorsSoni, Sachin (Author) / Karady, George G. (Thesis advisor) / Undrill, John (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2014
Description
Everyday speech communication typically takes place face-to-face. Accordingly, the task of perceiving speech is a multisensory phenomenon involving both auditory and visual information. The current investigation examines how visual information influences recognition of dysarthric speech. It also explores where the influence of visual information is dependent upon age. Forty adults participated in the study that measured intelligibility (percent words correct) of dysarthric speech in auditory versus audiovisual conditions. Participants were then separated into two groups: older adults (age range 47 to 68) and young adults (age range 19 to 36) to examine the influence of age. Findings revealed that all participants, regardless of age, improved their ability to recognize dysarthric speech when visual speech was added to the auditory signal. The magnitude of this benefit, however, was greater for older adults when compared with younger adults. These results inform our understanding of how visual speech information influences understanding of dysarthric speech.
ContributorsFall, Elizabeth (Author) / Liss, Julie (Thesis advisor) / Berisha, Visar (Committee member) / Gray, Shelley (Committee member) / Arizona State University (Publisher)
Created2014
Description
The problem of cooperative radar and communications signaling is investigated. Each system typically considers the other system a source of interference. Consequently, the tradition is to have them operate in orthogonal frequency bands. By considering the radar and communications operations to be a single joint system, performance bounds on a receiver that observes communications and radar return in the same frequency allocation are derived. Bounds in performance of the joint system is measured in terms of data information rate for communications and radar estimation information rate for the radar. Inner bounds on performance are constructed.
ContributorsChiriyath, Alex (Author) / Bliss, Daniel W (Thesis advisor) / Kosut, Oliver (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014
Description
Head movement is known to have the benefit of improving the accuracy of sound localization for humans and animals. Marmoset is a small bodied New World monkey species and it has become an emerging model for studying the auditory functions. This thesis aims to detect the horizontal and vertical rotation of head movement in marmoset monkeys.
Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.
Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection.
The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per second. In comparison, the natural alert signal - door opening and closing - evoked the faster head turns than other stimulus conditions. These results suggest that behaviorally relevant stimulus such as alert signals evoke faster head-turn responses in marmoset monkeys.
ContributorsSimhadri, Sravanthi (Author) / Zhou, Yi (Thesis advisor) / Turaga, Pavan (Thesis advisor) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014