The development of low-frequency sonar systems, using for instance a network of autonomous systems in unmanned vehicles, provides a practical means for bistatic measurements (i.e. when the source and receiver are widely separated) allowing for multiple viewpoints of the target of interest. Time-frequency analysis, in particular Wigner-Ville analysis, takes advantage of the evolution time dependent aspect of the echo spectrum to differentiate a man-made target (e.g. elastic spherical shell) from a natural one of the similar shape (e.g. solid). A key energetic feature of fluid loaded and thin spherical shell is the coincidence pattern, or mid-frequency enhancement echoes (MFE), that result from antisymmetric Lamb-waves propagating around the circumference of the shell. This thesis investigates numerically the bistatic variations of the MFE (with respect to the monostatic configuration) using the Wigner-Ville analysis. The observed time-frequency shifts of the MFE are modeled using a previously derived quantitative ray theory for spherical shell's scattering. Additionally, the advantage of an optimal array beamformer, based on joint time delays and frequency shifts (over a conventional time-delay beamformer) is illustrated for enhancing the detection of the MFE recorded across a bistatic receiver array.

In this dissertation, multicarrier schemes are reviewed within the framework of Gabor Systems. Their fundamental elements; what to transmit, i.e., symbols, how to transmit, i.e., filters or pulse shape, and where/when to transmit, i.e., lattices are investigated extensively. The relations between different types of multicarrier schemes are discussed. Within the framework of Gabor systems, a new windowing approach, edge windowing, is developed to address the out-of-band (OOB) radiation problem of orthogonal frequency division multiplexing (OFDM) based multicarrier schemes. To the best of our knowledge, for the first time, the diversity on the range of the users is exploited to suppress the sidelobes of OFDM. In addition to that, the concept of using different filters in OFDM structure is proposed. Besides the improvement on the OOB radiation performance of OFDM via edge windowing, conventional lattice structure of OFDM frame is enhanced considering the diversity in the network. The lattice structure of an OFDM frame is designed based on the statistical characteristics of the range of the users and the mobility. The concept of channel-aware frame structure is developed, which allows more efficient and reliable transmission. In addition to the aforementioned improvements on OFDM, interference issues in uncoordinated networks are addressed in this dissertation considering different multicarrier schemes. It is stressed that the interference from other links in the network sharing the same spectrum might degrade the link performance between the devices in an uncoordinated network, significantly. Considering the degradation due to other-user interference, the concept of partially overlapping tones (POT) is proposed. With the concept of partially overlapping tones, the interference energy observed at the victim receiver is mitigated via an intentional frequency offset between the links. The usefulness of intentional frequency offset to combat with the asynchronous nature of other-user interference without any timing constraint between interfering signals is emphasized. To the best of our knowledge, for the first time, the efficacy of non-orthogonal schemes are shown along with POT to address the other-user interference, which relies on the fact that self-interference problem is easier than other-user interference problem in an uncoordinated network. In the last part of this dissertation, required number of equalizer taps for multicarrier schemes is investigated to address the potential self-interference problems (e.g. due to the non-orthogonal multicarrier schemes with the concept of POT). Composite impact of transmit pulse shape, communication medium, and receive filter on the characteristics of the interference among the symbols in time and frequency is analyzed. It is emphasized that while taking less number of taps into account for the channel estimation causes lack of description of the composite effect, using more number of taps folds the noise into the estimated channel. The number of interfering symbols and their locations are obtained in both time and frequency for a given multicarrier scheme and signal-to-noise ratio. It is shown that correct number of taps yields not only improvement on BER performance but also less complex equalizer structures in practice.

Time-frequency analysis techniques are proposed as a necessary tool for the analysis of acoustics generated by helicopter transient maneuvering flight. Such techniques are necessary as the acoustic signals related to transient maneuvers are inherently unsteady. The wavelet transform is proposed as an appropriate tool, and it is compared to the more standard short-time Fourier transform technique through an investigation using several appropriately sized interrogation windows. It is shown that the wavelet transform provides a consistent spectral representation, regardless of employed window size. The short-time Fourier transform, however, provides spectral amplitudes that are highly dependent on the size of the interrogation window, and so is not an appropriate tool for this situation. An extraction method is also proposed to investigate blade-vortex interaction noise emitted during helicopter transient maneuvering flight. The extraction method allows for the investigation of blade-vortex interactions independent of other sound sources. The method is based on filtering the spectral data calculated through the wavelet transform technique. The filter identifies blade-vortex interactions through their high amplitude, high frequency impulsive content. The filtered wavelet coefficients are then inverse transformed to create a pressure signature solely related to blade-vortex interactions. This extraction technique, along with a prescribed wake model, is applied to experimental data extracted from three separate flight maneuvers performed by a Bell 430 helicopter. The maneuvers investigated include a steady level flight, fast- and medium-speed advancing side roll maneuvers. A sensitivity analysis is performed in order to determine the optimal tuning parameters employed by the filtering technique. For the cases studied, the optimized tuning parameters were shown to be frequencies above 7 main rotor harmonics, and amplitudes stronger than 25% (−6 dB) of the energy in the main rotor harmonic. Further, it is shown that blade-vortex interactions can be accurately extracted so long as the blade-vortex interaction peak energy signal is greater or equal to the energy in the main rotor harmonic. An in-depth investigation of the changes in the blade-vortex interaction signal during transient advancing side roll maneuvers is then conducted. It is shown that the sound pressure level related to blade-vortex interactions, shifts from the advancing side, to the retreating side of the vehicle during roll entry. This shift is predicted adequately by the prescribed wake model. However, the prescribed wake model is shown to be inadequate for the prediction of blade-vortex interaction miss distance, as it does not respond to the roll rate of the vehicle. It is further shown that the sound pressure levels are positively linked to the roll rate of the vehicle. Similar sound pressure level directivities and amplitudes can be seen when vehicle roll rates are comparable. The extraction method is shown to perform admirably throughout each maneuver. One limitation with the technique is identified, and a proposal to mitigate its effects is made. The limitation occurs when the main rotor harmonic energy drops below an arbitrary threshold. When this happens, a decreased spectral amplitude is required for filtering; which leads to the extraction of high frequency noise unrelated to blade-vortex interactions. It is shown, however, that this occurs only when there are no blade-vortex interactions present. Further, the resulting sound pressure level is identifiable as it is significantly less than the peak blade-vortex interaction sound pressure level. Thus the effects of this limitation are shown to be negligible. / text

Blind source separation methods such as independent component analysis (ICA) and second order blind identification (SOBI) have shown considerable potential in the area of ambient vibration system identification. The objective of these methods is to separate the modal responses, or sources, from the measured output responses, without the knowledge of excitation. Several frequency domain and time domain methods have been proposed and successfully implemented in the literature. Whereas frequency-domain methods pose several challenges typical of dealing with signals in the frequency-domain, popular time-domain methods such as NExT/ERA and SSI pose limitations in dealing with noise, low sensor density, modes having low energy content, or in dealing with systems having closely-spaced modes, such as those found in structures with passive energy dissipation devices, for example, tuned mass dampers.Motivated by these challenges, the current research focuses on developing methods to address the problem of separability of sources with low energy content, closely-spaced modes, and under-determined blind identification, that is, when the number of response measurements is less than the number of sources. These methods, requiring the time and frequency diversities of the measured outputs, are referred to as hybrid time and time-frequency source separation methods. The hybrid methods are classified into two categories. In the first one, the basic principles of modified SOBI are extended using the stationary wavelet transform (SWT) in order to improve the separability of sources, thereby improving the quality of identification. In the second category, empirical mode decomposition is employed to extract the intrinsic mode functions from measurements, followed by an estimation of the mode shape matrix using iterative and/or non iterative procedures within the framework of modified-SOBI. Both experimental and large-scale structural simulation results are included to demonstrate the applicability of these hybrid approaches to structural system identification problems.

No description available.

In our daily lives, we often make decisions that require the use of self-control, weighing trade-offs between various attributes: for example, selecting a food based on its health rather than its taste. Previous research suggests that re-weighting attributes may rely on selective attention, associated with decreased neural oscillations over posterior brain regions in the alpha (8-12 Hz) frequency range. Here, we utilized the high temporal resolution and whole-brain coverage of electroencephalography (EEG) to test this hypothesis in data collected from hungry human subjects exercising dietary self-control. Prior analysis of this data has found time-locked neural activity associated with each food’s perceived taste and health properties from approximately 400 to 650 ms after stimulus onset (Harris et al., 2013). We conducted time-frequency analyses to examine the role of alpha-band oscillations in this attribute weighting. Specifically, we predicted that there would be decreased alpha power in posterior electrodes beginning approximately 400 ms after stimulus onset for the presentation of healthy food relative to unhealthy food, reflecting shifts in selective attention. Consistent with this hypothesis, we found a significant decrease in alpha power for presentations of healthy relative to unhealthy foods. As predicted, this effect was most pronounced at posterior occipital and parietal electrodes and was significant from approximately 450 to 700 ms post-stimulus onset. Additionally, we found significant alpha-band decreases in right temporal electrodes during these times. These results extend previous attention research to multi-attribute choice, suggesting that the re-weighting of attributes can be measured neuro-computationally.

Este trabalho trata de conceitos relacionados à qualidade da Energia Elétrica (EE) e, neste contexto, apresenta a proposta de técnicas para a compressão da representação de transitórios rápidos e da análise tempo-frequência de distúrbios elétricos em geral. A qualidade da Energia Elétrica é medida pelo coeficiente de desvios que os sinais de tensão e corrente apresentam em relação ao sinal senoidal ideal. Tais desvios são denominados de distúrbios, podendo ser classificados como quase estacionários (e.g. distorção de harmônicas) e eventos (e.g. transitórios rápidos). No contexto de EE, os transitórios rápidos possuem pequena duração (i.e. na ordem dos microssegundos), são detectados por altas taxas de amostragem (i.e. na ordem dos MHz) e possuem difícil parametrização. Portanto, as representações das formas de onda geralmente são armazenadas para auxiliar a avaliação subjetiva dos transitórios e dos parâmetros de interesse. Consequentemente, a compressão destas formas de onda torna-se de extrema importância para armazenar dados adquiridos por longos períodos de tempo, e estes modos de compressão são tratados nesta dissertação. Em virtude das altas taxas de amostragem utilizadas, uma técnica baseada em Análise de Componentes Principais (PCA – Principal Component Analysis) é proposta para esta representação mais compacta de transitórios. Resultados mostram que o desempenho em compressão versus qualidade de reconstrução é semelhante ao de trabalhos relacionados com a vantagem de atender aos requisitos de altas taxas de amostragem. A análise tempo-frequência é um mecanismo que auxilia na classificação e caracterização dos distúrbios elétricos. Neste trabalho, a Transformada de Hilbert-Huang é estudada e uma proposta de melhoria na Decomposição Empírica de Modos (EMD – Empirical Mode Decomposition) é apresentada. Nossos resultados mostram que a técnica proposta economiza o custo computacional se comparada com o estado da arte. Em virtude disso, a técnica proposta apresenta uma taxa de redução no tempo médio de execução de 99,76 % em relação à técnica do estado da arte. Além disso, uma verificação acerca do desempenho em eficiência de compressão versus qualidade de reconstrução de trabalhos anteriores é também desenvolvida nesta dissertação. Foi utilizada uma sistemática de avaliação experimental com base em amostras de sinais AC, de forma a avaliar as taxas de compressão atingidas pelas técnicas estudadas, como a Transformada Wavelet Discreta. Resultados mostram que a Transformada Wavelet falha para compressão de todo e qualquer tipo de distúrbio elétrico quando analisado o compromisso entre acuidade de reconstrução versus eficiência de compressão. / This work deals with concepts related to the AC Power Quality theoretical framework and, in this scope, proposes techniques for the representation of fast transient data compression and for the power line disturbances time-frequency analysis. The AC power quality is measured by the differences between actual and ideal sinusoidal voltage/current signals. These differences are known as electrical disturbances, which can be classified as quasi-stationary (e.g. harmonic distortion) or events (e.g. surge or fast transients) disturbances. In the AC Power Quality scope, the fast transients have short duration (i.e. typically on the order of microseconds), are detected by high sampling rates (i.e. typically on the order of MHz), and are hard to characterize and parameterize. Hence, the resultant representation of the waveforms is in general stored to help in the subjective evaluation of these fast transients and their parameters of interest. As a consequence the compression turns out to be of main concern, in order to store this information acquired over long periods of time (like weeks or months). In this work, a compression technique is proposed taking into account the high sampling rates. The proposed technique makes use of the Principal Component Analysis (PCA) for such compact representation of fast transients. The Compression efficiency versus reconstruction accuracy results show a similar performance for the proposed technique when compared to the related works. On the other hand, the proposed technique can handle the large amount of data provided by the high sampling rates. The time-frequency analysis helps in the classification and characterization of AC power quality disturbances. In this work, the Hilbert-Huang Transform is studied and a modification is proposed in order to improve the Empirical Mode Decomposition (EMD) performance. Our results show that the proposed modification can save computational cost when compared to the state-of-the-art. Therefore, the average execution time is reduced to 99.76 % in comparison with the state-of-the-art technique. Besides that, this work also revisits previous techniques based on the Discrete Wavelet Transform (DWT) in order to verify the trade-off between reconstruction accuracy versus compression efficiency under a more systematic experimental evaluation setup, considering samples of real AC signals. Results show that DWT fails as a general-purpose technique in AC Power Quality scope.

Este trabalho trata de conceitos relacionados à qualidade da Energia Elétrica (EE) e, neste contexto, apresenta a proposta de técnicas para a compressão da representação de transitórios rápidos e da análise tempo-frequência de distúrbios elétricos em geral. A qualidade da Energia Elétrica é medida pelo coeficiente de desvios que os sinais de tensão e corrente apresentam em relação ao sinal senoidal ideal. Tais desvios são denominados de distúrbios, podendo ser classificados como quase estacionários (e.g. distorção de harmônicas) e eventos (e.g. transitórios rápidos). No contexto de EE, os transitórios rápidos possuem pequena duração (i.e. na ordem dos microssegundos), são detectados por altas taxas de amostragem (i.e. na ordem dos MHz) e possuem difícil parametrização. Portanto, as representações das formas de onda geralmente são armazenadas para auxiliar a avaliação subjetiva dos transitórios e dos parâmetros de interesse. Consequentemente, a compressão destas formas de onda torna-se de extrema importância para armazenar dados adquiridos por longos períodos de tempo, e estes modos de compressão são tratados nesta dissertação. Em virtude das altas taxas de amostragem utilizadas, uma técnica baseada em Análise de Componentes Principais (PCA – Principal Component Analysis) é proposta para esta representação mais compacta de transitórios. Resultados mostram que o desempenho em compressão versus qualidade de reconstrução é semelhante ao de trabalhos relacionados com a vantagem de atender aos requisitos de altas taxas de amostragem. A análise tempo-frequência é um mecanismo que auxilia na classificação e caracterização dos distúrbios elétricos. Neste trabalho, a Transformada de Hilbert-Huang é estudada e uma proposta de melhoria na Decomposição Empírica de Modos (EMD – Empirical Mode Decomposition) é apresentada. Nossos resultados mostram que a técnica proposta economiza o custo computacional se comparada com o estado da arte. Em virtude disso, a técnica proposta apresenta uma taxa de redução no tempo médio de execução de 99,76 % em relação à técnica do estado da arte. Além disso, uma verificação acerca do desempenho em eficiência de compressão versus qualidade de reconstrução de trabalhos anteriores é também desenvolvida nesta dissertação. Foi utilizada uma sistemática de avaliação experimental com base em amostras de sinais AC, de forma a avaliar as taxas de compressão atingidas pelas técnicas estudadas, como a Transformada Wavelet Discreta. Resultados mostram que a Transformada Wavelet falha para compressão de todo e qualquer tipo de distúrbio elétrico quando analisado o compromisso entre acuidade de reconstrução versus eficiência de compressão. / This work deals with concepts related to the AC Power Quality theoretical framework and, in this scope, proposes techniques for the representation of fast transient data compression and for the power line disturbances time-frequency analysis. The AC power quality is measured by the differences between actual and ideal sinusoidal voltage/current signals. These differences are known as electrical disturbances, which can be classified as quasi-stationary (e.g. harmonic distortion) or events (e.g. surge or fast transients) disturbances. In the AC Power Quality scope, the fast transients have short duration (i.e. typically on the order of microseconds), are detected by high sampling rates (i.e. typically on the order of MHz), and are hard to characterize and parameterize. Hence, the resultant representation of the waveforms is in general stored to help in the subjective evaluation of these fast transients and their parameters of interest. As a consequence the compression turns out to be of main concern, in order to store this information acquired over long periods of time (like weeks or months). In this work, a compression technique is proposed taking into account the high sampling rates. The proposed technique makes use of the Principal Component Analysis (PCA) for such compact representation of fast transients. The Compression efficiency versus reconstruction accuracy results show a similar performance for the proposed technique when compared to the related works. On the other hand, the proposed technique can handle the large amount of data provided by the high sampling rates. The time-frequency analysis helps in the classification and characterization of AC power quality disturbances. In this work, the Hilbert-Huang Transform is studied and a modification is proposed in order to improve the Empirical Mode Decomposition (EMD) performance. Our results show that the proposed modification can save computational cost when compared to the state-of-the-art. Therefore, the average execution time is reduced to 99.76 % in comparison with the state-of-the-art technique. Besides that, this work also revisits previous techniques based on the Discrete Wavelet Transform (DWT) in order to verify the trade-off between reconstruction accuracy versus compression efficiency under a more systematic experimental evaluation setup, considering samples of real AC signals. Results show that DWT fails as a general-purpose technique in AC Power Quality scope.

abstract: Structural integrity is an important characteristic of performance for critical components used in applications such as aeronautics, materials, construction and transportation. When appraising the structural integrity of these components, evaluation methods must be accurate. In addition to possessing capability to perform damage detection, the ability to monitor the level of damage over time can provide extremely useful information in assessing the operational worthiness of a structure and in determining whether the structure should be repaired or removed from service. In this work, a sequential Bayesian approach with active sensing is employed for monitoring crack growth within fatigue-loaded materials. The monitoring approach is based on predicting crack damage state dynamics and modeling crack length observations. Since fatigue loading of a structural component can change while in service, an interacting multiple model technique is employed to estimate probabilities of different loading modes and incorporate this information in the crack length estimation problem. For the observation model, features are obtained from regions of high signal energy in the time-frequency plane and modeled for each crack length damage condition. Although this observation model approach exhibits high classification accuracy, the resolution characteristics can change depending upon the extent of the damage. Therefore, several different transmission waveforms and receiver sensors are considered to create multiple modes for making observations of crack damage. Resolution characteristics of the different observation modes are assessed using a predicted mean squared error criterion and observations are obtained using the predicted, optimal observation modes based on these characteristics. Calculation of the predicted mean square error metric can be computationally intensive, especially if performed in real time, and an approximation method is proposed. With this approach, the real time computational burden is decreased significantly and the number of possible observation modes can be increased. Using sensor measurements from real experiments, the overall sequential Bayesian estimation approach, with the adaptive capability of varying the state dynamics and observation modes, is demonstrated for tracking crack damage. / Dissertation/Thesis / Ph.D. Electrical Engineering 2013

Este trabalho trata de conceitos relacionados à qualidade da Energia Elétrica (EE) e, neste contexto, apresenta a proposta de técnicas para a compressão da representação de transitórios rápidos e da análise tempo-frequência de distúrbios elétricos em geral. A qualidade da Energia Elétrica é medida pelo coeficiente de desvios que os sinais de tensão e corrente apresentam em relação ao sinal senoidal ideal. Tais desvios são denominados de distúrbios, podendo ser classificados como quase estacionários (e.g. distorção de harmônicas) e eventos (e.g. transitórios rápidos). No contexto de EE, os transitórios rápidos possuem pequena duração (i.e. na ordem dos microssegundos), são detectados por altas taxas de amostragem (i.e. na ordem dos MHz) e possuem difícil parametrização. Portanto, as representações das formas de onda geralmente são armazenadas para auxiliar a avaliação subjetiva dos transitórios e dos parâmetros de interesse. Consequentemente, a compressão destas formas de onda torna-se de extrema importância para armazenar dados adquiridos por longos períodos de tempo, e estes modos de compressão são tratados nesta dissertação. Em virtude das altas taxas de amostragem utilizadas, uma técnica baseada em Análise de Componentes Principais (PCA – Principal Component Analysis) é proposta para esta representação mais compacta de transitórios. Resultados mostram que o desempenho em compressão versus qualidade de reconstrução é semelhante ao de trabalhos relacionados com a vantagem de atender aos requisitos de altas taxas de amostragem. A análise tempo-frequência é um mecanismo que auxilia na classificação e caracterização dos distúrbios elétricos. Neste trabalho, a Transformada de Hilbert-Huang é estudada e uma proposta de melhoria na Decomposição Empírica de Modos (EMD – Empirical Mode Decomposition) é apresentada. Nossos resultados mostram que a técnica proposta economiza o custo computacional se comparada com o estado da arte. Em virtude disso, a técnica proposta apresenta uma taxa de redução no tempo médio de execução de 99,76 % em relação à técnica do estado da arte. Além disso, uma verificação acerca do desempenho em eficiência de compressão versus qualidade de reconstrução de trabalhos anteriores é também desenvolvida nesta dissertação. Foi utilizada uma sistemática de avaliação experimental com base em amostras de sinais AC, de forma a avaliar as taxas de compressão atingidas pelas técnicas estudadas, como a Transformada Wavelet Discreta. Resultados mostram que a Transformada Wavelet falha para compressão de todo e qualquer tipo de distúrbio elétrico quando analisado o compromisso entre acuidade de reconstrução versus eficiência de compressão. / This work deals with concepts related to the AC Power Quality theoretical framework and, in this scope, proposes techniques for the representation of fast transient data compression and for the power line disturbances time-frequency analysis. The AC power quality is measured by the differences between actual and ideal sinusoidal voltage/current signals. These differences are known as electrical disturbances, which can be classified as quasi-stationary (e.g. harmonic distortion) or events (e.g. surge or fast transients) disturbances. In the AC Power Quality scope, the fast transients have short duration (i.e. typically on the order of microseconds), are detected by high sampling rates (i.e. typically on the order of MHz), and are hard to characterize and parameterize. Hence, the resultant representation of the waveforms is in general stored to help in the subjective evaluation of these fast transients and their parameters of interest. As a consequence the compression turns out to be of main concern, in order to store this information acquired over long periods of time (like weeks or months). In this work, a compression technique is proposed taking into account the high sampling rates. The proposed technique makes use of the Principal Component Analysis (PCA) for such compact representation of fast transients. The Compression efficiency versus reconstruction accuracy results show a similar performance for the proposed technique when compared to the related works. On the other hand, the proposed technique can handle the large amount of data provided by the high sampling rates. The time-frequency analysis helps in the classification and characterization of AC power quality disturbances. In this work, the Hilbert-Huang Transform is studied and a modification is proposed in order to improve the Empirical Mode Decomposition (EMD) performance. Our results show that the proposed modification can save computational cost when compared to the state-of-the-art. Therefore, the average execution time is reduced to 99.76 % in comparison with the state-of-the-art technique. Besides that, this work also revisits previous techniques based on the Discrete Wavelet Transform (DWT) in order to verify the trade-off between reconstruction accuracy versus compression efficiency under a more systematic experimental evaluation setup, considering samples of real AC signals. Results show that DWT fails as a general-purpose technique in AC Power Quality scope.