Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

The scintillating fiber focal plane detector for the use of Kaos as a double arm spectrometer

The upgrade of the Mainz Mikrotron (MAMI) electron accelerator facility in 2007 which raised the beam energy up to 1.5,GeV, gives the opportunity to study strangeness production channels through electromagnetic process. The Kaon Spectrometer (KAOS) managed by the A1 Collaboration, enables the efficient detection of the kaons associated with strangeness electroproduction. Used as a single arm spectrometer, it can be combined with the existing high-resolution spectrometers for exclusive measurements in the kinematic domain accessible to them.rnrnFor studying hypernuclear production in the ^A Z(e,e'K^+) _Lambda ^A(Z-1) reaction, the detection of electrons at very forward angles is needed. Therefore, the use of KAOS as a double-arm spectrometer for detection of kaons and the electrons at the same time is mandatory. Thus, the electron arm should be provided with a new detector package, with high counting rate capability and high granularity for a good spatial resolution. To this end, a new state-of-the-art scintillating fiber hodoscope has been developed as an electron detector.rnrnThe hodoscope is made of two planes with a total of 18432 scintillating double-clad fibers of 0.83 mm diameter. Each plane is formed by 72 modules. Each module is formed from a 60deg slanted multi-layer bundle, where 4 fibers of a tilted column are connected to a common read out. The read-out is made with 32 channels of linear array multianode photomultipliers. Signal processing makes use of newly developed double-threshold discriminators. The discriminated signal is sent in parallel to dead-time free time-to-digital modules and to logic modules for triggering purposes.rnrnTwo fiber modules were tested with a carbon beam at GSI, showing a time resolution of 220 ps (FWHM) and a position residual of 270 microm m (FWHM) with a detection efficiency epsilon>99%.rnrnThe characterization of the spectrometer arm has been achieved through simulations calculating the transfer matrix of track parameters from the fiber detector focal plane to the primary vertex. This transfer matrix has been calculated to first order using beam transport optics and has been checked by quasielastic scattering off a carbon target, where the full kinematics is determined by measuring the recoil proton momentum. The reconstruction accuracy for the emission parameters at the quasielastic vertex was found to be on the order of 0.3 % in first test realized.rnrnThe design, construction process, commissioning, testing and characterization of the fiber hodoscope are presented in this work which has been developed at the Institut für Kernphysik of the Johannes Gutenberg - Universität Mainz.

Speech Enhancement With Inventory Style Speech Resynthesis

We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted signal we are resynthesizing a new “clean” signal based on its likely characteristics. These characteristics are estimated from the distorted signal. A successful implementation of the proposed method is presented. Experiments were performed in a scenario with roughly one hour of clean speech training data. Our results show that the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments. Potential applications for the proposed method include jet cockpit communication systems and offline methods for the restoration of audio recordings.

Efficient computation of discrete polynomial transforms

This letter presents a new recursive method for computing discrete polynomial transforms. The method is shown for forward and inverse transforms of the Hermite, binomial, and Laguerre transforms. The recursive flow diagrams require only 2 additions, 2( +1) memory units, and +1multipliers for the +1-point Hermite and binomial transforms. The recursive flow diagram for the +1-point Laguerre transform requires 2 additions, 2( +1) memory units, and 2( +1) multipliers. The transform computation time for all of these transforms is ( )

On a Microcomputer Implementation of an Intrusion-detection Algorithm

The main objective of this paper is to discuss various aspects of implementing a specific intrusion-detection scheme on a micro-computer system using fixed-point arithmetic. The proposed scheme is suitable for detecting intruder stimuli which are in the form of transient signals. It consists of two stages: an adaptive digital predictor and an adaptive threshold detection algorithm. Experimental results involving data acquired via field experiments are also included.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.

A new approach to detect structural differences in lung parenchyma using digital image analysis

Morphometric investigations using a point and intersection counting strategy in the lung often are not able to reveal the full set of morphologic changes. This happens particularly when structural modifications are not expressed in terms of volume density changes and when rough and fine surface density alterations cancel each other at different magnifications. Making use of digital image processing, we present a methodological approach that allows to easily and quickly quantify changes of the geometrical properties of the parenchymal lung structure and reflects closely the visual appreciation of the changes. Randomly sampled digital images from light microscopic sections of lung parenchyma are filtered, binarized, and skeletonized. The lung septa are thus represented as a single-pixel wide line network with nodal points and end points and the corresponding internodal and end segments. By automatically counting the number of points and measuring the lengths of the skeletal segments, the lung architecture can be characterized and very subtle structural changes can be detected. This new methodological approach to lung structure analysis is highly sensitive to morphological changes in the parenchyma: it detected highly significant quantitative alterations in the structure of lungs of rats treated with a glucocorticoid hormone, where the classical morphometry had partly failed.

Application of Signal Advance Technology to Electrophysiology

Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.

TDOA for Narrow-band Signal with Low Sampling Rate and Imperfect Synchronization

Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

Stable isotope ratios and chemistry on corals from the Caribbean Sea

Instrumental climate data are limited in length and only available with low spatial coverage before the middle of the 20th century. This is too short to reliably determine and interpret decadal and longer scale climate variability and to understand the underlying mechanisms with sufficient accuracy. A proper knowledge of past variability of the climate system is needed to assess the anthropogenic impact on climate and ecosystems, and also important with regard to long-range climate forecasting. Highly-resolved records of past climate variations that extend beyond pre-industrial times can significantly help to understand long-term climate changes and trends. Indirect information on past environmental and climatic conditions can be deduced from climate-sensitive proxies. Large colonies of massive growing tropical reef corals have been proven to sensitively monitor changes in ambient seawater. Rapid skeletal growth, typically ranging between several millimeters to centimeters per year, allows the development of proxy records at sub-seasonal resolution. Stable oxygen isotopic composition and trace elemental ratios incorporated in the aragonitic coral skeleton can reveal a detailed history of past environmental conditions, e.g., sea surface temperature (SST). In general, coral-based reconstructions from the tropical Atlantic region have lagged behind the extensive work published using coral records from the Indian and Pacific Oceans. Difficulties in the analysis of previously utilized coral archives from the Atlantic, typically corals of the genera Montastrea and Siderastrea, have so far exacerbated the production of long-term high-resolution proxy records. The objective of this study is the evaluation of massive fast-growing corals of the species Diploria strigosa as a new marine archive for climate reconstructions from the tropical Atlantic region. For this purpose, coral records from two study sites in the eastern Caribbean Sea (Guadeloupe, Lesser Antilles; and Archipelago Los Roques, Venezuela) were examined. At Guadeloupe, a century-long monthly resolved multi-proxy coral record was generated. Results present the first d18O (Sr/Ca)-SST calibration equations for the Atlantic braincoral Diploria strigosa, that are robust and consistent with previously published values using other coral species from different regions. Both proxies reflect local variability of SST on a sub-seasonal scale, which is a precondition for studying seasonally phase-locked climate variations, as well as track variability on a larger spatial scale (i.e., in the Caribbean and tropical North Atlantic). Coral Sr/Ca reliably records local annual to interannual temperature variations and is higher correlated to in-situ air temperature than to grid-SST. The warming calculated from coral Sr/Ca is concurrent with the strong surface temperature increase at the study site during the past decades. Proxy data show a close relationship to major climate signals from the tropical Pacific and North Atlantic (the El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO)) affecting the seasonal cycle of SST in the North Tropical Atlantic (NTA). Coral oxygen isotopes are also influenced by seawater d18O (d18Osw) which is linked to the hydrological cycle, and capture large-scale climate variability in the NTA region better than Sr/Ca. Results from a quantitative comparison between extreme events in the two most prominent modes of external forcing, namely the ENSO and NAO, and respective events recorded in seasonal coral d18O imply that SST variability at the study site is highly linked to Pacific and North Atlantic variability, by this means supporting the assumptions of observational- and model-based studies which suggest a strong impact of ENSO and NAO forcings onto the NTA region through a modulation of trade wind strength in winter. Results from different spectral analysis tools suggest that interannual climate variability recorded by the coral proxies is II largely dictated by Pacific ENSO forcing, whereas at decadal and longer timescales the influence of the NAO is dominan. tThe Archipelago Los Roques is situated in the southeastern Caribbean Sea, north of the Venezuelan coast. Year-to-year variations in monthly resolved coral d18O of a nearcentury- long Diploria strigosa record are significantly correlated with SST and show pronounced multidecadal variations. About half of the variance in coral d18O can be explained by variations in seawater d18O, which can be estimated by calculating the d18Oresidual via subtracting the SST component from measured coral d18O. The d18Oresidual and a regional precipitation index are highly correlated at low frequencies, suggesting that d18Osw variations are primarily atmospheric-driven. Warmer SSTs at Los Roques broadly coincide with higher precipitation in the southeastern Caribbean at multidecadal time scales, effectively strengthening the climate signal in the coral d18O record. The Los Roques coral d18O record displays a strong and statistically significant relationship to different indices of hurricane activity during the peak of the Atlantic hurricane season in boreal summer and is a particularly good indicator of decadal-multidecadal swings in the latter indices. In general, the detection of long-term changes and trends in Atlantic hurricane activity is hampered due to the limited length of the reliable instrumental record and the known inhomogeneity in the observational databases which result from changes in observing practice and technology over the years. The results suggest that coral-derived proxy data from Los Roques can be used to infer changes in past hurricane activity on timescales that extend well beyond the reliable record. In addition, the coral record exhibits a clear negative trend superimposed on the decadal to multidecadal cycles, indicating a significant warming and freshening of surface waters in the genesis region of tropical cyclones during the past decades. The presented coral d18O time series provides the first and, so far, longest continuous coral-based record of hurricane activity. It appears that the combination of both signals (SST and d18Osw) in coral d18O leads to an amplification of large-scale climate signals in the record, and makes coral d18O even a better proxy for hurricane activity than SST alone. Atlantic hurricane activity naturally exhibits strong multidecadal variations that are associated with the Atlantic Multidecadal Oscillation (AMO), the major mode of lowfrequency variability in the North Atlantic Ocean. However, the mechanisms underlying this multidecadal variability remain controversial, primarily because of the limited instrumental record. The Los Roques coral d18O displays strong multidecadal variability with a period of approximately 60 years that is closely related to the AMO, making the Archipelago Los Roques a very sensitive location for studying low-frequency climate variability in the Atlantic Ocean. In summary, the coral records presented in this thesis capture different key climate variables in the north tropical Atlantic region very well, indicating that fast-growing Diploria strigosa corals represent a promising marine archive for further proxy-based reconstructions of past climate variability on a range of time scales.

Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques

This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

Descripción, comparación y ejemplos de uso de las funciones de la toolbox de procesado digital de imágenes de MATLAB®

Matlab, uno de los paquetes de software matemático más utilizados actualmente en el mundo de la docencia y de la investigación, dispone de entre sus muchas herramientas una específica para el procesado digital de imágenes. Esta toolbox de procesado digital de imágenes está formada por un conjunto de funciones adicionales que amplían la capacidad del entorno numérico de Matlab y permiten realizar un gran número de operaciones de procesado digital de imágenes directamente a través del programa principal. Sin embargo, pese a que MATLAB cuenta con un buen apartado de ayuda tanto online como dentro del propio programa principal, la bibliografía disponible en castellano es muy limitada y en el caso particular de la toolbox de procesado digital de imágenes es prácticamente nula y altamente especializada, lo que requiere que los usuarios tengan una sólida formación en matemáticas y en procesado digital de imágenes. Partiendo de una labor de análisis de todas las funciones y posibilidades disponibles en la herramienta del programa, el proyecto clasificará, resumirá y explicará cada una de ellas a nivel de usuario, definiendo todas las variables de entrada y salida posibles, describiendo las tareas más habituales en las que se emplea cada función, comparando resultados y proporcionando ejemplos aclaratorios que ayuden a entender su uso y aplicación. Además, se introducirá al lector en el uso general de Matlab explicando las operaciones esenciales del programa, y se aclararán los conceptos más avanzados de la toolbox para que no sea necesaria una extensa formación previa. De este modo, cualquier alumno o profesor que se quiera iniciar en el procesado digital de imágenes con Matlab dispondrá de un documento que le servirá tanto para consultar y entender el funcionamiento de cualquier función de la toolbox como para implementar las operaciones más recurrentes dentro del procesado digital de imágenes. Matlab, one of the most used numerical computing environments in the world of research and teaching, has among its many tools a specific one for digital image processing. This digital image processing toolbox consists of a set of additional functions that extend the power of the digital environment of Matlab and allow to execute a large number of operations of digital image processing directly through the main program. However, despite the fact that MATLAB has a good help section both online and within the main program, the available bibliography is very limited in Castilian and is negligible and highly specialized in the particular case of the image processing toolbox, being necessary a strong background in mathematics and digital image processing. Starting from an analysis of all the available functions and possibilities in the program tool, the document will classify, summarize and explain each function at user level, defining all input and output variables possible, describing common tasks in which each feature is used, comparing results and providing illustrative examples to help understand its use and application. In addition, the reader will be introduced in the general use of Matlab explaining the essential operations within the program and clarifying the most advanced concepts of the toolbox so that an extensive prior formation will not be necessary. Thus, any student or teacher who wants to start digital image processing with Matlab will have a document that will serve to check and understand the operation of any function of the toolbox and also to implement the most recurrent operations in digital image processing.

Rectangular room dimensions estimation using narrowband signal and sectorized antennas

A system for estimation of unknown rectangular room dimensions based on two radio transceivers, both capable of full duplex operations, is presented. The approach is based on CIR measurements taken at the same place where the signal is transmitted (generated), commonly known as self- to-self CIR. Another novelty is the receiver antenna design which consists of eight sectorized antennas with 45° aperture in the horizontal plane, whose total coverage corresponds to the isotropic one. The dimensions of a rectangular room are reconstructed directly from radio impulse responses by extracting the information regarding features like round trip time, received signal strength and reverberation time. Using radar approach the estimation of walls and corners positions are derived. Additionally, the analysis of the absorption coefficient of the test environment is conducted and a typical coefficient for office room with furniture is proposed. Its accuracy is confirmed through the results of volume estimation. Tests using measured data were performed, and the simulation results confirm the feasibility of the approach.

Analysis and design of multirate synchronous sampling schemes for sparse multiband signals

We consider the problem of developing efficient sampling schemes for multiband sparse signals. Previous results on multicoset sampling implementations that lead to universal sampling patterns (which guarantee perfect reconstruction), are based on a set of appropriate interleaved analog to digital converters, all of them operating at the same sampling frequency. In this paper we propose an alternative multirate synchronous implementation of multicoset codes, that is, all the analog to digital converters in the sampling scheme operate at different sampling frequencies, without need of introducing any delay. The interleaving is achieved through the usage of different rates, whose sum is significantly lower than the Nyquist rate of the multiband signal. To obtain universal patterns the sampling matrix is formulated and analyzed. Appropriate choices of the parameters, that is the block length and the sampling rates, are also proposed.