A comparative study of two-dimensional modeling methods for electromagnetic scattering data

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2007.Thesis (Master's) -- Bilkent University, 2007.Includes bibliographical references leaves 60-62.The aim of this research is to model two-dimensional data encountered in electromagnetic scattering problems using model-based parameter estimation techniques. Once a highly accurate model is constructed from a few samples, the model can then be used to interpolate between or extrapolate from the original samples at any desired point and any number of times, thus reducing the amount of data needed to be stored in memory or required to be measured. An added advantage is that the computations required to be carried out on the numerical samples can instead be carried out on the analytical model, which may reduce the computational complexity. It is intuitive that a higher number of terms in the model, increases the accuracy, but additionally it has the unwanted effect of increasing the computational complexity and memory requirement as well. An additional goal, therefore, is to solve the optimization problem of obtaining a model by maximizing the accuracy and minimizing the number of terms. Several modeling techniques are compared in this study, especially those based on matrix pencil methods. Some techniques for optimizing their performance have also been suggested. The pros and cons of each method are also discussed. It is shown that using the suggested techniques provides us with better models, but some pointers are also provided towards investigating more viable alternatives.Srinivasan, Anirudh SM.S

Electroencephalogram Signalling diagnosis using Softcomputing

The two most frightening things for the researchers in clinical signal processing and computer aided diagnosis are noise and relativity of human judgment. The researchers made effort to overcome these two challenges by using various soft computing approaches. In this article the present benefits of these approaches in the accomplishment of the analysis of electroencephalogram (EEG) is acknowledge. There is also the presentation of the significance of several trend and prospects of further softcomputing methods that can produce better results in signal processing of EEG. Medical experts apply the different softcomputing techniques for disease diagnoses and decision making systems performed on brain actions and modeling of neural impulses of the human encephalon

Sparse multidimensional exponential analysis with an application to radar imaging

We present a d-dimensional exponential analysis algorithm that offers a range of advantages compared to other methods. The technique does not suffer the curse of dimensionality and only needs O((d + 1)n) samples for the analysis of an n-sparse expression. It does not require a prior estimate of the sparsity n of the d-variate exponential sum. The method can work with sub-Nyquist sampled data and offers a validation step, which is very useful in low SNR conditions. A favourable computation cost results from the fact that d independent smaller systems are solved instead of one large system incorporating all measurements simultaneously. So the method also lends itself easily to a parallel execution. Our motivation to develop the technique comes from 2D and 3D radar imaging and is therefore illustrated on such examples

Site Amplification and Attenuation via Downhole Array Seismogram Inversion: A Comparative Study of the 2003 Miyagi-Oki Aftershock Sequence

Weak-motion geotechnical array recordings at 38 stations of the Japanese strong-motion network KiK-Net from the 2003 M_w 7:0 Miyagi-Oki aftershock sequence are used here to quantify the amplification and attenuation effects of near-surface formations to incident seismic motion. Initially, a seismic waveform optimization algorithm is implemented for the evaluation of high-resolution, low-strain velocity (V_s), attenuation (Q_s), and density (ρ) profiles at the sites of interest. Based on the inversion results, V_s versus Q_s correlations are developed, and scattering versus intrinsic attenuation effects are accounted for in their physical interpretation. Surface-to-downhole traditional spectral ratios (SSR), cross-spectral ratios (c-SSR), and horizontal-to-vertical (H/V) site-response estimates are next evaluated and compared, while their effectiveness is assessed as a function of the site conditions classified on the basis of the weighted average Vs of the upper 30 m (V_(s30)) of the formations. Single and reference-station site-response estimates are successively compared to surface-to-rock outcrop amplification spectra and are evaluated by deconvolution of the downhole records based on the inversion results; comparison of the observed SSR and estimated surface-to-rock outcrop amplification spectra illustrates the effects of destructive interference of downgoing waves at the downhole instrument level as a function of the site class. Site amplification factors are successively computed in reference to the National Earthquake Hazards Reduction Program (NEHRP) B–C boundary site conditions (V_(s30) = 760 m/sec), and results are compared to published values developed on the basis of strong-motion data and site-response analyses. Finally, weak-motion SSR estimates are compared to the mainshock spectra, and conclusions are drawn for the implications of soil nonlinearity in the near surface. Results presented in this article suggest that currently employed site classification criteria need to be reevaluated to ensure intraclass consistency in the assessment of amplification potentials and nonlinearity susceptibility of near-surficial soil formations

Earth Fault Distance Computation Methods Based on Transients in Power Distribution Systems

The most common fault type in MV distribution network is single line to earth fault. The initial transients of earth faults are important especially for unearthed and compensated neutral networks. The earth fault transient signals consist of many different frequency components, which result from charging and discharging of the network capacitances. The transient components provide valuable information for fault location purposes. The charging component has higher amplitude and lower frequency than the discharge component and hence is more suitable to be used for fault location purposes. In this thesis, we discuss algorithms to locate an earth fault in unearthed or a compensated neutral MV networks using the information of the measured transient signal. The networks considered are assumed to be radially operated and they are modeled using Electromagnetic Transient Program-Alternative Transient Program (EMTP-ATP). Five types of fault location algorithms have been developed which are called general model (GM) algorithm, exact model (EM) algorithm, continuous wavelet transform (CWT) based method, multiple regression analysis (MRA) based method and artificial neural network (ANN). GM algorithm is developed based on a simplified model of symmetrical components while EM algorithm is developed with exact "pi"-model of symmetrical components. Both algorithms utilize the frequency of charging transient to estimate the fault distance. CWT based algorithm requires both voltage and current of transient signals to estimate the fault path inductance. MRA and NN algorithms were developed using the transient signal measured from the secondary side of the MV/LV distribution transformer. In addition, an algorithm to find a correct path towards the position of fault in network which has many branches is presented. The results from intensive simulations and experiments in actual distribution networks are also presented in this thesis. The results are analyzed using signal processing techniques. The algorithms apply continuous wavelet transform (CWT) to locate the dominant charge transient frequency and extract the specific coefficient corresponding to the charge transient frequency. In this thesis, the properties of Hilbert transformation (HT) are used to estimate the damping attenuation of the transient signal. Finally the performance of the proposed fault location algorithms is evaluated and the results are compared. Based on the simulation results, it is found that the proposed algorithms work at a reasonable level of accuracy. The results from real experiment data show that both CWT and GM algorithms have a comparable result

Adaptive Parameter Estimation of Power System Dynamic Models Using Modal Information

Knowledge of the parameter values of the dynamic generator models is of paramount importance for creating accurate models for power system dynamics studies. Traditionally, power systems consists of a relatively limited numbers of large power stations and the values of generator parameters were provided by manufacturers and validated by utilities. Recently however, with the increasing penetration of distributed generation, the accuracy of these models and parameters cannot be guaranteed. This thesis addresses the above concerns by developing a methodology to estimate the parameter values of a power system dynamic model online, employing dynamic system modes, i.e. modal frequencies and damping. The dynamic modes are extracted from real-time measurements. The aim of the proposed methodology is to minimise the differences between the observed and modelled modes of oscillation. It should be emphasised that the proposed methodology does not aim to develop the dynamic model itself but rather modify its parameter using WAMS measurements. The developed methodology is general and can be used to identify any generator parameters., However, thesis concentrates on the estimation of generator inertia constants. The results suggest that the proposed methodology can estimate inertias and replicate the dynamic behaviour of the power system accurately, through the inclusion of pseudo-measurements in the optimisation process. The pseudo-measurements not only improves the accuracy of the parameter estimation but also the robustness of it. Observability, a problem when there are fewer numbers of measurements than the numbers of parameters to be estimated, has also been successfully tackled. It has been shown that the damping measurements do not influence the accuracy and robustness of generator inertia estimation significantly

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