158 research outputs found

    Enhancements to the Generalized Sidelobe Canceller for Audio Beamforming in an Immersive Environment

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    The Generalized Sidelobe Canceller is an adaptive algorithm for optimally estimating the parameters for beamforming, the signal processing technique of combining data from an array of sensors to improve SNR at a point in space. This work focuses on the algorithm’s application to widely-separated microphone arrays with irregular distributions used for human voice capture. Methods are presented for improving the performance of the algorithm’s blocking matrix, a stage that creates a noise reference for elimination, by proposing a stochastic model for amplitude correction and enhanced use of cross correlation for phase correction and time-difference of arrival estimation via a correlation coefficient threshold. This correlation technique is also applied to a multilateration algorithm for an efficient method of explicit target tracking. In addition, the underlying microphone array geometry is studied with parameters and guidelines for evaluation proposed. Finally, an analysis of the stability of the system is performed with respect to its adaptation parameters

    Structural health monitoring of non-linear hysteretic structures.

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    Ensuring life safety is the primary design and maintenance requirement for civil structures designed to be serviceable for a specific lifetime. However, structures subjected to a number of factors may experience quicker or more gradual deterioration than anticipated, or even a premature loss of function. Scheduled visual inspection is the oldest and most commonly used damage monitoring technique, but has significant disadvantages when quick damage assessment and certainty are needed, such as after a major seismic event. Quick, accurate and quantitative determination of the damage state is vital following an earthquake, to estimate damage, remaining life-time, and ensure safe re-occupancy, if possible. Rapid development of sensor technology and increasing computing power has enabled continuous structural monitoring using various sensing techniques. The measured data can be analyzed using structural health monitoring (SHM) methods. SHM refers to all elements of the process of identifying mechanical properties of a structural system, comparing it with previous states, detecting changes/abnormalities, and relating these to damage. A successful SHM method should be able to automatically identify and locate damage after large, non-linear response events. The majority of existing, primarily vibration based, SHM techniques have serious limitations in situations where a quick, accurate, and quantitative assessment is needed. More specifically, many SHM techniques perform well when structures behave linearly and are subjected to ambient loads, but this does not apply to earthquake events. Moreover, some methods can only work off-line, involve significant computational effort and/or human input, and/or do not provide any indication of damage location and/or severity. To address these limitations, this thesis explores the application of a novel SHM implementation strategy composed of a novel modal parameter identification and its subsequent application to a proven hysteresis loop analysis (HLA) method. The study demonstrates the proposed strategy can be readily used to track the performance of non-linear degrading structures subjected to strong ground motion, essentially in real-time and without human input. Thus, the proposed tools can be used to support/replace visual inspection results, reduce downtime, minimize business disruptions and, most importantly, maximize life safety. More specifically, this thesis proposes and analyses the application of a novel modal parameter identification technique, which performs in near real-time and, most importantly, is efficient when approximating non-linear structures subjected to relatively short duration ground motion inputs. The technique operates in modal space and is based on a pre-defined optimization process, which decouples frequency response spectra of interfering, generally higher frequency, modes. Optimization can be realized over relatively short time windows to provide continuous monitoring of highly non-linear, degrading structures. In particular, identified modal parameters can be readily used to identify damage. However, modal parameters can have very poor sensitivity to damage and are often difficult to interpret. Thus, it is challenging to infer the location and severity of damage based on detected changes/variation in modal parameters alone. In this research, the identified time-varying modal parameters are used to decompose the structural response and reconstruct single mode dominant restoring force-deformation hysteresis loops, which can be readily analyzed using recently developed hysteresis loops analysis (HLA). The versatility and robustness of HLA has been explored in a number of studies. However, the analyzed case structures employed in these validation cases exhibited very small contribution from the higher modes, which typically can cause significant irregularities, and make effective implementation of HLA more problematic. Hence, this thesis aims to improve the robustness of HLA, using mode segregation and reconstruction of single mode dominant, regular shape hysteresis loops from non-linear structural response. First, this research develops a modal parameter output-only identification technique, which is validated for a simple time-invariant linear structure. Second, the output-only method is extended to an input-output method enabling operators to carry out near-real time identification of non-linear structures, which is validated for a simple time-varying non-linear structure. Third, the input-output method is validated using the simulation results of a more complex non-linear multi-degree-of-freedom structure, formulated using fiber elements. Finally, the proposed SHM strategy, consisting of continuous modal parameter identification and subsequent application of HLA is validated for two experimental non-linear structures. Overall, this thesis proposes a novel system identification technique, which performs outputonly identification of linear structures and, more importantly, provides input-output real-time modal parameter tracking of highly non-linear structures. Thus, the method extends the application of modal SHM methods to non-linear cases. The proposed technique performs successfully without operator input and can be easily automated to provide continuous modal tracking and damage detection. The technique performs both as stand-alone for damage detection and in combination with HLA for damage quantification as demonstrated for highly non-linear cases

    An investigation into current and vibration signatures of three phase induction motors

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    This research aimed at investigating the relationship between three phase induction motors vibration (MVS) and current signatures (MCS). This is essential due to the cost of vibration measuring equipment and in cases where vibration of interest point is not accessible; such as electrical submersible pumps (ESP) used in oil industry. A mathematical model was developed to understand the effects of two types of induction motors common faults; rotor bar imperfections and phase imbalance on the motor vibration and current signatures. An automated test facility was developed in which 1.1 kW three phase motor could be tested under varying shaft rotation speeds and loads for validating the developed model. Time and frequency domains statistical parameters of the measured signals were calculated for fault detection and assessing its severity. The measured signals were also processed using the short time Fourier transform (STFT), the Wigner-Ville distribution (WVD), the continuous wavelet transform (CWT) and discrete wavelet transform (DWT) and wavelet multi-resolution analysis (MRA). The non-stationary components, representing faults within induction motor measured vibration and current signals, were successfully detected using wavelet decomposition technique. An effective alternative to direct vibration measurement scheme, based on radial basis function networks, was developed to the reconstruction of motor vibration using measurements of one phase of the motor current. It was found that this method captured the features of induction motor faults with reasonable degrees of accuracy. Another method was also developed for the early detection and diagnosis of faults using an enhanced power factor method. Experimental results confirmed that the power factor can be used successfully for induction motor fault diagnosis and is also promising in assessing fault severity. The suggested two methods offer inexpensive, reliable and non-intrusive condition monitoring tools that suits real-time applications. Directions for further work were also outlined

    Advanced receiver structures for mobile MIMO multicarrier communication systems

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    Beyond third generation (3G) and fourth generation (4G) wireless communication systems are targeting far higher data rates, spectral efficiency and mobility requirements than existing 3G networks. By using multiple antennas at the transmitter and the receiver, multiple-input multiple-output (MIMO) technology allows improving both the spectral efficiency (bits/s/Hz), the coverage, and link reliability of the system. Multicarrier modulation such as orthogonal frequency division multiplexing (OFDM) is a powerful technique to handle impairments specific to the wireless radio channel. The combination of multicarrier modulation together with MIMO signaling provides a feasible physical layer technology for future beyond 3G and fourth generation communication systems. The theoretical benefits of MIMO and multicarrier modulation may not be fully achieved because the wireless transmission channels are time and frequency selective. Also, high data rates call for a large bandwidth and high carrier frequencies. As a result, an important Doppler spread is likely to be experienced, leading to variations of the channel over very short period of time. At the same time, transceiver front-end imperfections, mobility and rich scattering environments cause frequency synchronization errors. Unlike their single-carrier counterparts, multi-carrier transmissions are extremely sensitive to carrier frequency offsets (CFO). Therefore, reliable channel estimation and frequency synchronization are necessary to obtain the benefits of MIMO OFDM in mobile systems. These two topics are the main research problems in this thesis. An algorithm for the joint estimation and tracking of channel and CFO parameters in MIMO OFDM is developed in this thesis. A specific state-space model is introduced for MIMO OFDM systems impaired by multiple carrier frequency offsets under time-frequency selective fading. In MIMO systems, multiple frequency offsets are justified by mobility, rich scattering environment and large angle spread, as well as potentially separate radio frequency - intermediate frequency chains. An extended Kalman filter stage tracks channel and CFO parameters. Tracking takes place in time domain, which ensures reduced computational complexity, robustness to estimation errors as well as low estimation variance in comparison to frequency domain processing. The thesis also addresses the problem of blind carrier frequency synchronization in OFDM. Blind techniques exploit statistical or structural properties of the OFDM modulation. Two novel approaches are proposed for blind fine CFO estimation. The first one aims at restoring the orthogonality of the OFDM transmission by exploiting the properties of the received signal covariance matrix. The second approach is a subspace algorithm exploiting the correlation of the channel frequency response among the subcarriers. Both methods achieve reliable estimation of the CFO regardless of multipath fading. The subspace algorithm needs extremely small sample support, which is a key feature in the face of time-selective channels. Finally, the Cramér-Rao (CRB) bound is established for the problem in order to assess the large sample performance of the proposed algorithms.reviewe

    Pattern Recognition

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    A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

    Virtual metrology for plasma etch processes.

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    Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

    Channel estimation and parameters acquisition systems employing cooperative diversity

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    Doutoramento em Engenharia Eletrotécnica e TelecomunicaçÔesThis work investigates new channel estimation schemes for the forthcoming and future generation of cellular systems for which cooperative techniques are regarded. The studied cooperative systems are designed to re-transmit the received information to the user terminal via the relay nodes, in order to make use of benefits such as high throughput, fairness in access and extra coverage. The cooperative scenarios rely on OFDM-based systems employing classical and pilot-based channel estimators, which were originally designed to pointto-point links. The analytical studies consider two relaying protocols, namely, the Amplifyand-Forward and the Equalise-and-Forward, both for the downlink case. The relaying channels statistics show that such channels entail specific characteristics that comply to a proper filter and equalisation designs. Therefore, adjustments in the estimation process are needed in order to obtain the relay channel estimates, refine these initial estimates via iterative processing and obtain others system parameters that are required in the equalisation. The system performance is evaluated considering standardised specifications and the International Telecommunication Union multipath channel models.Este trabalho tem por objetivo o estudo de novos esquemas de estimação de canal para sistemas de comunicação móvel das próximas geraçÔes, para os quais técnicas cooperativa são consideradas. Os sistemas cooperativos investigados neste trabalho estão projetados para fazerem uso de terminais adicionais a fim de retransmitir a informação recebida para o utilizador final. Desta forma, pode-se usurfruir de benefícios relacionados às comunicaçÔes cooperativas tais como o aumento do rendimento do sistema, fiabilidade e extra cobertura. Os cenårios são basedos em sistemas OFDM que empregam estimadores de canal que fazem uso de sinais piloto e que originalmente foram projetados para ligaçÔes ponto a ponto. Os estudos analíticos consideram dois protocolos de encaminhamento, nomeadamente, Amplify-and-Forward e Equalise-and-Forward, ambos para o caso downlink. As estatísticas dos canais em estudo mostram que tais canais ocasionam características específicas para as quais o filtro do estimador e a equalisação devem ser apropridamente projetados. Estas características requerem ajustes que são necessårios no processo de estimação a fim de estimar os canais, refinar as estimativas iniciais através de processos iterativos e ainda obter outros parùmetros do sistema que são necessårios na equalização. O desempenho dos esquemas propostos são avaliados tendo em consideração especificaçÔes padronizadas e modelos de canal descritos na International Telecommunication Union

    Virtual metrology for plasma etch processes.

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    Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

    Interferometric synthetic aperture sonar system supported by satellite

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    Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200
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