Wide-area Situational Awareness Application Developments

This dissertation expands the topics from the wide-area situational awareness application development, system architecture design, to power system disturbance analysis. All the works are grounded on the wide-area Frequency Monitoring Network (FNET). The FNET system takes GPS-synchronized wide-area measurements in a low-cost, easily deployable manner at 120V single-phase power outlet. These synchronized observations enables the monitoring of bulk power systems, and provides critical information for understanding power system disturbances and system operations. Firstly, the work addresses the viability of angle measurement to serve different types of situational awareness applications, including the development of new angle-based event location estimation methods, the design of real-time system visualization framework using angle measurement. Secondly, a sound FNET power system event monitoring and automatic event reporting system framework is introduced, with NERC Frequency Response Initiative (FRI) tasks included to improve power system situational awareness capability. Lastly, the work covers different types of power system disturbance analysis, including the statistical analysis of frequency disturbances in NA power grid from 2008 to 2011; analysis of typical frequency response characteristics of the generation and load loss events in Europe power grid; analysis of some major disturbances in NA power grid from 2010 to 2011; and the inter-area oscillation modal analysis in the WECC system

On the Characteristic Polynomial of Regular Linear Matrix Pencil

Linear matrix pencil, denoted by (A,B), plays an important role in control systems and numerical linear algebra. The problem of finding the eigenvalues of (A,B) is often solved numerically by using the well-known QZ method. Another approach for exploring the eigenvalues of (A,B) is by way of its characteristic polynomial, P(λ)=A − λB. There are other applications of working directly with the characteristic polynomial, for instance, using Routh-Hurwitz analysis to count the stable roots of P(λ) and transfer function representation of control systems governed by differential-algebraic equations. In this paper, we present an algorithm for algebraic construction of the characteristic polynomial of a regular linear pencil. The main theorem reveals a connection between the coefficients of P(λ) and a lexicographic combination of the rows between matrices A and B

Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Development and Application of a Method for Unwrapping Single Images of Cylindrical Objects

The goal of this project was to create a software tool to unwrap digital images of cylindrical rock cores and also to create a tool to measure the accuracy of the unwrapping transform. Measurements of an object can be taken directly from an image if the object is planar and the image plane of the camera is perpendicular to the object. If these conditions are met then picture scale allows a user to relate measurements in the image to a real world coordinate system after correcting for radial distortion. But if the object in the image is not planar or is not perpendicular to the image plane then additional corrections or geometric transformations must be applied to the object in the image. The project is focused on creating a coded software solution, using digital images from an off the shelf-camera, to transform or unwrap single images of cylindrical rock cores so that all objects in the image are co-planar. In addition to tools created to unwrap digital images a second software tool was created to verify the accuracy of the unwrapping software. The project is broken down into three major components. The first is a technique for taking pictures of rock core, or image acquisition. A single rock core is wrapped with a paper grid pattern that is used to determine a pixel scale for a series of images of a rock core sample. The grid wrapped core is placed in a carriage made of a set of two rollers. This carriage is then centered below a camera that is remotely controlled from a desktop computer. Two halogen lights are used to evenly illuminate the surface of the core and an image is taken. Once the grid pattern is photographed the pattern is removed and a series of images of the outer surface of the core are taken. The next phase of the unwrapping is to take the original image and pass it through a series of software modules that will assist the user to perform a rectification of the original images. First the scale of each pixel in the image is found using images of the original grid pattern wrapped around the core. Next the core itself is isolated from other background objects present in each image. Then a geometric transform is applied to the image of the core, using the unique pixel scale, with the goal to unwrap each image so that all objects in the image are co-planar and no longer suffer any distortion. In order to measure the effectiveness of this transform on rectifying all areas of the image, a second software tool was created. This software tool allows the user the ability to measure the spacing of gridlines in the original image of the grid wrapped core and compare these measurements to the same image after it has been unwrapped. The code returns a database of measurements for every gridline present in a image as well as different plots of the data for the user to make final conclusions as to the effectiveness of unwrapping on each area of the core images

Validated exponential analysis for harmonic sounds

In audio spectral analysis, the Fourier method is popular because of its stability and its low computational complexity. It suffers however from a time-frequency resolution trade off and is not particularly suited for aperiodic signals such as exponentially decaying ones. To overcome their resolution limitation, additional techniques such as quadratic peak interpolation or peak picking, and instantaneous frequency computation from phase unwrapping are used. Parametric methods on the other hand, overcome the time frequency trade off but are more susceptible to noise and have a higher computational complexity. We propose a method to overcome these drawbacks: we set up regularized smaller sized independent problems and perform a cluster analysis on their combined output. The new approach validates the true physical terms in the exponential model, is robust in the presence of outliers in the data and is able to filter out any non-physical noise terms in the model. The method is illustrated in the removal of electrical humming in harmonic sounds

High-sensitivity interferometry

High-sensitivity interferometric techniques are considered for non-destructive testing applications. The methods enable quantitative measurement of optical path variations, resulting from dynamic changes within the test object. [Continues.

Application of the Non-Hermitian Singular Spectrum Analysis to the exponential retrieval problem

We present a new approach to solve the exponential retrieval problem. We derive a stable technique, based on the singular value decomposition (SVD) of lag-covariance and crosscovariance matrices consisting of covariance coefficients computed for index translated copies of an initial time series. For these matrices a generalized eigenvalue problem is solved. The initial signal is mapped into the basis of the generalized eigenvectors and phase portraits are consequently analyzed. Pattern recognition techniques could be applied to distinguish phase portraits related to the exponentials and noise. Each frequency is evaluated by unwrapping phases of the corresponding portrait, detecting potential wrapping events and estimation of the phase slope. Efficiency of the proposed and existing methods is compared on the set of examples, including the white Gaussian and auto-regressive model noise

Quantitative interior x-ray nanotomography by a hybrid imaging technique

Hierarchical structures appear often in life and materials sciences, and their characterization profits greatly from imaging methods that allow seamless probing of various length scales without sacrificing image quality. X-ray tomography is particularly adept at probing 3D structures; however, zooming in on a region of interest results in a loss of quantitativeness of image contrast and suffers from artifacts unless a priori knowledge or assumptions about the sample are used. Here, we demonstrate a hybrid technique that exploits a micrometer-resolution overview to realize ab initio nanoscale interior tomography with quantitative contrast. In a study of avian eggshell, a model for bionanoporous materials, our approach reveals a complex arrangement of vesicles with sizes ranging from hundred nanometers to a few micrometers. We anticipate that such an approach can be widely adopted and benefited from at synchrotron and laboratory sources, for instance, where such zooming capabilities are already present or can be readily realized