Digital signal processing implementation for near real-time wavelet transformation system for binary images

Communication has become an essential function in our civilization. With the increasing demand for communication channels, it is now necessary to find ways to optimize the use of their bandwidth. One way to achieve this is by transforming the information before it is transmitted. This transformation can be performed by several techniques. One of the newest of these techniques is the use of wavelets. Wavelet transformation refers to the act of breaking down a signal into components called details and trends by using small waveforms that have a zero average in the time domain. After this transformation the data can be compressed by discarding the details, transmitting the trends. In the receiving end, the trends are used to reconstruct the image. In this work, the wavelet used for the transformation of an image will be selected from a library of available bases. The accuracy of the reconstruction, after the details are discarded, is dependent on the wavelets chosen from the wavelet basis library. The system developed in this thesis takes a 2-D image and decomposes it using a wavelet bank. A digital signal processor is used to achieve near real-time performance in this transformation task. A contribution of this thesis project is the development of DSP-based test bed for the future development of new real-time wavelet transformation algorithms.

Proteção diferencial de transformadores de potência utilizando a transformada Wavelet

About 10% of faults involving the electrical system occurs in power transformers. Therefore, the protection applied to the power transformers is essential to ensure the continuous operation of this device and the efficiency of the electrical system. Among the protection functions applied to power transformers, the differential protection appears as one of the main schemes, presenting reliable discrimination between internal faults and external faults or inrush currents. However, when using the low frequency components of the differential currents flowing through the transformer, the main difficulty of the conventional methods of differential protection is the delay for detection of the events. However, internal faults, external faults and other disturbances related to the transformer operation present transient and can be appropriately detected by the wavelet transform. In this paper is proposed the development of a wavelet-based differential protection for detection and identification of external faults to the transformer, internal faults, and transformer energizing by using the wavelet coefficient energy of the differential currents. The obtained results reveal the advantages of using of the wavelet transform in the differential protection compared to conventional protection, since it provides reliability and speed in detection of these events.

Estimação de potência em tempo real utilizando a transformada wavelet

The goal of the power monitoring in electrical power systems is to promote the reliablility as well as the quality of electrical power.Therefore, this dissertation proposes a new theory of power based on wavelet transform for real-time estimation of RMS voltages and currents, and some power amounts, such as active power, reactive power, apparent power, and power factor. The appropriate estimation the of RMS and power values is important for many applications, such as: design and analysis of power systems, compensation devices for improving power quality, and instruments for energy measuring. Simulation and experimental results obtained through the proposed MaximalOverlap Discrete Wavelet Transform-based method were compared with the IEEE Standard 1459-2010 and the commercial oscilloscope, respectively, presenting equivalent results. The proposed method presented good performance for compact mother wavelet, which is in accordance with real-time applications.

Modeling the impact of large-scale solid mass transfers on the gravity field

The focus of this thesis is to explore and quantify the response of large-scale solid mass transfer events on satellite-based gravity observations. The gravity signature of large-scale solid mass transfers has not been deeply explored yet; mainly due to the lack of significant events during dedicated satellite gravity missions‘ lifespans. In light of the next generation of gravity missions, the feasibility of employing satellite gravity observations to detect submarine and surface mass transfers is of importance for geoscience (improves the understanding of geodynamic processes) and for geodesy (improves the understanding of the dynamic gravity field). The aim of this thesis is twofold and focuses on assessing the feasibility of using satellite gravity observations for detecting large-scale solid mass transfers and on modeling the impact on the gravity field caused by these events. A methodology that employs 3D forward modeling simulations and 2D wavelet multiresolution analysis is suggested to estimate the impact of solid mass transfers on satellite gravity observations. The gravity signature of various submarine and subaerial events that occurred in the past was estimated. Case studies were conducted to assess the sensitivity and resolvability required in order to observe gravity differences caused by solid mass transfers. Simulation studies were also employed in order to assess the expected contribution of the Next Generation of Gravity Missions for this application.

Propuesta sostenible para mitigar los efectos climáticos adversos en una ciudad costera de Argentina

Los indicadores de sostenibilidad climática constituyen herramientas fundamentales para complementar las políticas de ordenamiento del territorio urbano y pueden beneficiar la calidad de vida sus habitantes. En el presente trabajo se diseñó un indicador climático urbano para la ciudad de Bahía Blanca considerando variables meteorológicas y análisis de la percepción social. El mismo permitió delimitar la ciudad en cuatro regiones bien diferenciadas entre sí. A partir de entonces, se realizó una propuesta sostenible para mitigar los efectos adversos del clima a partir de la aplicación del método DPSIR. Las mismas estuvieron destinadas a mejorar las condiciones de vida de la población. Los resultados permitieron considerar que una pronta implementación de la misma junto con una activa participación de los actores sociales y los tomadores de decisiones es necesaria para mejorar las condiciones actuales en la que se encuentra la ciudad. Con las medidas propuestas, la población local sabrá cómo actuar ante la ocurrencia de distintos eventos extremos, eventos de desconfort climático, etc. Al ser un método sencillo, la metodología aplicada en este estudio puede replicarse en otras ciudades del mundo con el objetivo de mejorar la calidad de vida de los habitantes.

Expedition in Data and Harmonic Analysis on Graphs

The graph Laplacian operator is widely studied in spectral graph theory largely due to its importance in modern data analysis. Recently, the Fourier transform and other time-frequency operators have been defined on graphs using Laplacian eigenvalues and eigenvectors. We extend these results and prove that the translation operator to the i’th node is invertible if and only if all eigenvectors are nonzero on the i’th node. Because of this dependency on the support of eigenvectors we study the characteristic set of Laplacian eigenvectors. We prove that the Fiedler vector of a planar graph cannot vanish on large neighborhoods and then explicitly construct a family of non-planar graphs that do exhibit this property. We then prove original results in modern analysis on graphs. We extend results on spectral graph wavelets to create vertex-dyanamic spectral graph wavelets whose support depends on both scale and translation parameters. We prove that Spielman’s Twice-Ramanujan graph sparsifying algorithm cannot outperform his conjectured optimal sparsification constant. Finally, we present numerical results on graph conditioning, in which edges of a graph are rescaled to best approximate the complete graph and reduce average commute time.

Transformada wavelet aplicada a análise automática de oscilografias de curta duração em unidades geradoras

The focus of this work is the automatic analysis of disturbance records for electrical power generating units. The main proposition is a method based on wavelet transform applied to short-term disturbance records (waveform records). The goal of the method is to detect the time instants of recorded disturbances and extract meaningful information that characterize the faults. The result is a set of representative information of the monitored signals in power generators. This information can be further classified by an expert system (or other classification method) in order to classify the faults and other abnormal operating conditions. The large amount of data produced by digital fault recorders during faults justify the research of methods to assist the analysts in their task of analysing the disturbances. The literature review pointed out the state of the art and possible applications for oscillography records. The review of the COMTRADE standard and wavelet transform underlines the choice of the method for solving the problem. The conducted tests lead to the determination of the best mother wavelet for the segmentation process. The application of the proposed method to five case studies with real oscillographic records confirmed the accuracy and efficiency of the proposed scheme. With this research, the post-operation analysis of occurrences is improved and as a direct result is the reduction of the time that generators are offline.

Monitoramento e identificação numérico e experimental de danos em vigas e pontes de aço e concreto utilizando transformadas de wavelet

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2015.

Análisis cuantitativo de técnicas de fusión de imágenes

La fusión de imágenes es un proceso que permite obtener una nueva imagen en base a la información que tienen dos o más imágenes, las cuales poseen distinta información de la misma escena, que se combina convenientemente en la nueva imagen fusionada. Para poder obtener esta imagen resultante se utilizan diversas técnicas, requiriéndose identificar las métricas más apropiadas que permitan determinar aquella técnica o técnicas que proporcionen el mejor resultado en términos de calidad de la nueva imagen con la información fusionada. Por tal motivo en el presente trabajo, se realiza un análisis comparativo sobre diversas técnicas de fusión, a saber: promedio simple, máximo/ mínimo valor, análisis de componentes principales, transformada de wavelets y pirámides laplaciana (contraste y morfológica). Cada una de ellas presenta un proceso distinto para el tratamiento de los píxeles correspondientes a las imágenes. Así mismo, se han seleccionado las siguientes métricas cuantitativas para verificar la calidad de las imágenes resultantes fusionadas: error cuadrático medio, relación señal a ruido de pico, contenido estructural, diferencia promedio, correlación cruzada normalizada y entropía.

Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Remoção de ruídos sísmicos utilizando transformada de wavelet 1D e 2D com software em desenvolvimento

In the Hydrocarbon exploration activities, the great enigma is the location of the deposits. Great efforts are undertaken in an attempt to better identify them, locate them and at the same time, enhance cost-effectiveness relationship of extraction of oil. Seismic methods are the most widely used because they are indirect, i.e., probing the subsurface layers without invading them. Seismogram is the representation of the Earth s interior and its structures through a conveniently disposed arrangement of the data obtained by seismic reflection. A major problem in this representation is the intensity and variety of present noise in the seismogram, as the surface bearing noise that contaminates the relevant signals, and may mask the desired information, brought by waves scattered in deeper regions of the geological layers. It was developed a tool to suppress these noises based on wavelet transform 1D and 2D. The Java language program makes the separation of seismic images considering the directions (horizontal, vertical, mixed or local) and bands of wavelengths that form these images, using the Daubechies Wavelets, Auto-resolution and Tensor Product of wavelet bases. Besides, it was developed the option in a single image, using the tensor product of two-dimensional wavelets or one-wavelet tensor product by identities. In the latter case, we have the wavelet decomposition in a two dimensional signal in a single direction. This decomposition has allowed to lengthen a certain direction the two-dimensional Wavelets, correcting the effects of scales by applying Auto-resolutions. In other words, it has been improved the treatment of a seismic image using 1D wavelet and 2D wavelet at different stages of Auto-resolution. It was also implemented improvements in the display of images associated with breakdowns in each Auto-resolution, facilitating the choices of images with the signals of interest for image reconstruction without noise. The program was tested with real data and the results were good

Wavelengths in bioconvection patterns

Unicellular bottom-heavy swimming microorganisms are usually denser than the fluid in which they swim. In shallow suspensions, the bottom heaviness results in a gravitational torque that orients the cells to swim vertically upwards in the absence of fluid flow. Swimming cells thus accumulate at the upper surface to form a concentrated layer of cells. When the cell concentration is high enough, the layer overturns to form bioconvection patterns. Thin concentrated plumes of cells descend rapidly and cells return to the upper surface in wide, slowly moving upwelling plumes. When there is fluid flow, a second viscous torque is exerted on the swimming cells. The balance between the local shear flow viscous and the gravitational torques determines the cells' swimming direction, (gyrotaxis). In this thesis, the wavelengths of bioconvection patterns are studied experimentally as well as theoretically as follow; First, in aquasystem it is rare to find one species lives individually and when they swim they can form complex patterns. Thus, a protocol for controlled experiments to mix two species of swimming algal cells of \emph{C. rienhardtii} and \emph{C. augustae} is systematically described and images of bioconvection patterns are captured. A method for analysing images using wavelets and extracting the local dominant wavelength in spatially varying patterns is developed. The variation of the patterns as a function of the total concentration and the relative concentration between two species is analysed. Second, the linear stability theory of bioconvection for a suspension of two mixed species is studied. The dispersion relationship is computed using Fourier modes in order to calculate the neutral curves as a function of wavenumbers $k$ and $m$. The neutral curves are plotted to compare the instability onset of the suspension of the two mixed species with the instability onset of each species individually. This study could help us to understand which species contributes the most in the process of pattern formation. Finally, predicting the most unstable wavelength was studied previously around a steady state equilibrium situation. Since assuming steady state equilibrium contradicts with reality, the pattern formation in a layer of finite depth of an evolving basic state is studied using the nonnormal modes approach. The nonnormal modes procedure identifies the optimal initial perturbation that can be obtained for a given time $t$ as well as a given set of parameters and wavenumber $k$. Then, we measure the size of the optimal perturbation as it grows with time considering a range of wavenumbers for the same set of parameters to be able to extract the most unstable wavelength.