117 resultados para RF signals


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The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

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The aim of this study was to determine if the carbohydrate (CHO) availability alters the rate of increase in the rating of perceived exertion (RPE) during high intensity exercise and whether this would be associated with physiological changes. Six males performed high intensity exercise after 48 h of controlled, high CHO (80%) and low CHO (10%) diets. Time to exhaustion was lower in the low compared to high CHO diet. The rate of increase in RPE was greater and the VO(2) slow component was lower in the low CHO diet than in the control. There was no significant condition effect for cortisol, insulin, pH, plasma glucose, potassium, or lactate concentrations. Multiple linear regression indicated that the total amplitude of VO(2) and perceived muscle strain accounted for the greatest variance in the rate of increase in RPE. These results suggest that cardiorespiratory variables and muscle strain are important afferent signals from the periphery for the RPE calculations.

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The evaluation of the electrical characteristics of technical HTS tapes are of the key importance in determining the design and operational features of superconducting power apparatuses as well as to understand the external factors which affect the superconducting performance. In this work we report the systematic measurements of the electric field versus current density, E-J relation of short samples for three commercial HTS tapes (BSCCO-2223 tapes, with and without steel reinforcement, and YBCO-coated conductor) at 77 K. In order to get sensitive and noiseless voltage signals the measurements were carried out with DC transport current and subjecting the broad surface tape to DC (0-300 mT) and AC (0-62 mT, 60 Hz) magnetic fields. The voltage is measured by a sensitive nanovoltmeter and the applied magnetic field is monitored by a Hall sensor placed on the tape broad surface. The comparison between the results obtained from the three tapes was done by fitting a power-law equation for currents in the vicinity of the critical current. For the current regime below the critical one a linear correlation of the electric field against the current density is observed. The BSCCO samples presented the same behavior, i.e., a decreasing of n-index with the increasing DC and AC magnetic field strength. Under AC field the decreasing slope of n-index is steeper as compared to DC field. The n-index curve for the YBCO tape showed similar behavior for AC field, however under DC field in the 0-390 mT range exhibited a slight decreasing of the n-index.

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This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

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This work presents the study and development of a combined fault location scheme for three-terminal transmission lines using wavelet transforms (WTs). The methodology is based on the low- and high-frequency components of the transient signals originated from fault situations registered in the terminals of a system. By processing these signals and using the WT, it is possible to determine the time of travelling waves of voltages and/or currents from the fault point to the terminals, as well as estimate the fundamental frequency components. A new approach presents a reliable and accurate fault location scheme combining some different solutions. The main idea is to have a decision routine in order to select which method should be used in each situation presented to the algorithm. The combined algorithm was tested for different fault conditions by simulations using the ATP (Alternative Transients Program) software. The results obtained are promising and demonstrate a highly satisfactory degree of accuracy and reliability of the proposed method.

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This paper presents a small-area CMOS current-steering segmented digital-to-analog converter (DAC) design intended for RF transmitters in 2.45 GHz Bluetooth applications. The current-source design strategy is based on an iterative scheme whose variables are adjusted in a simple way, minimizing the area and the power consumption, and meeting the design specifications. A theoretical analysis of static-dynamic requirements and a new layout strategy to attain a small-area current-steering DAC are included. The DAC was designed and implemented in 0.35 mu m CMOS technology, requiring an active area of just 200 mu m x 200 mu m. Experimental results, with a full-scale output current of 700 mu A and a 3.3 V power supply, showed a spurious-free dynamic range of 58 dB for a 1 MHz output sine wave and sampling frequency of 50 MHz, with differential and integral nonlinearity of 0.3 and 0.37 LSB, respectively.

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The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

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The productivity associated with commonly available disassembly methods today seldomly makes disassembly the preferred end-of-life solution for massive take back product streams. Systematic reuse of parts or components, or recycling of pure material fractions are often not achievable in an economically sustainable way. In this paper a case-based review of current disassembly practices is used to analyse the factors influencing disassembly feasibility. Data mining techniques were used to identify major factors influencing the profitability of disassembly operations. Case characteristics such as involvement of the product manufacturer in the end-of-life treatment and continuous ownership are some of the important dimensions. Economic models demonstrate that the efficiency of disassembly operations should be increased an order of magnitude to assure the competitiveness of ecologically preferred, disassembly oriented end-of-life scenarios for large waste of electric and electronic equipment (WEEE) streams. Technological means available to increase the productivity of the disassembly operations are summarized. Automated disassembly techniques can contribute to the robustness of the process, but do not allow to overcome the efficiency gap if not combined with appropriate product design measures. Innovative, reversible joints, collectively activated by external trigger signals, form a promising approach to low cost, mass disassembly in this context. A short overview of the state-of-the-art in the development of such self-disassembling joints is included. (c) 2008 CIRP.

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On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

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Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

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In this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear H(infinity) approaches. Two nonlinear H(infinity) controllers that guarantee induced L(2)-norm, between input (disturbances) and output signals, bounded by an attenuation level gamma, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experimental results are presented, with a comparative study among these robust control strategies and the standard computed torque, plus proportional-derivative, controller.

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Low Intensity Electrical Stimulation (LIES) has been used for bone repair, but little is known about its effects on bone after menopause. Osteocytes probably play a role in mediating this physical stimulus and they could act as transducers through the release of biochemical signals, such as nitric oxide (NO). The aim of the present study was to investigate the effects of LIES on bone structure and remodeling, NOS expression and osteocyte viability in ovariectomized (OVX) rats. Thirty rats (200-220 g) were divided into 3 groups: SHAM, OVX, and OVX subjected to LIES (OVX + LIES) for 12 weeks. Following the protocol, rats were sacrificed and tibias were collected for histomorphometric analysis and immunohistochemical detection of endothelial NO synthase (eNOS), inducible NOS (iNOS), and osteocyte apoptosis (caspase-3 and TUNEL). OVX rats showed significant (p < 0.05 vs. SHAM) decreased bone volume (10% vs. 25%) and trabecular number (1.7 vs. 3.9), and increased eroded surfaces (4.7% vs. 3.2%) and mineralization surfaces (15.9% vs. 7.7%). In contrast, after LIES, all these parameters were significantly different from OVX but not different from SHAM. eNOS and iNOS were similarly expressed in subperiosteal regions of tibiae cortices of SHAM, not expressed in OVX, and similarly expressed in OVX + LIES when compared to SHAM. In OVX, the percentage of apoptotic osteocytes (24%) was significantly increased when compared to SHAM (11%) and OVX + LIES (8%). Our results suggest that LIES counteracts some effects of OVX on bone tissue preserving bone structure and microarchitecture, iNOS and eNOS expression, and osteocyte viability.

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Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

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The aim of this work is to study the wheel/workpiece dynamic interactions in high-speed grinding using vitrified CBN wheel and DTG (difficult to grind) work materials. This problem is typical in the grinding of engine valve heads. The influence of tangential force per abrasive grain was investigated as an important control variable for the determination of G ratio. Experiments were carried out to observe the influence of vibrations in the wheel wear. The measurements of acoustic emission (AE) and vibration signals helped in identifying the correlation between the dynamic interactions (produced by forced random excitation) and the wheel wear. The wheel regenerative chatter phenomenon was observed by using the wheel mapping technique. (c) 2008 CIRP.

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This research presents the development and implementation in a computational routine of algorithms for fault location in multiterminal transmission lines. These algorithms are part of a fault-location system, which is capable of correctly identifying the fault point based on voltage and current phasor quantities, calculated by using measurements of voltage and current signals from intelligent electronic devices, located on the transmission-line terminals. The algorithms have access to the electrical parameters of the transmission lines and to information about the transformers loading and their connection type. This paper also presents the development of phase component models for the power system elements used by the fault-location algorithms.