10 resultados para power cable testing

em Aston University Research Archive


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Citation information: Armstrong RA, Davies LN, Dunne MCM & Gilmartin B. Statistical guidelines for clinical studies of human vision. Ophthalmic Physiol Opt 2011, 31, 123-136. doi: 10.1111/j.1475-1313.2010.00815.x ABSTRACT: Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or 'non-standard' analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and 'power', hypothesis testing, parametric and non-parametric variables, 'bootstrap methods', one and two-tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.

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Many papers claim that a Log Periodic Power Law (LPPL) model fitted to financial market bubbles that precede large market falls or 'crashes', contains parameters that are confined within certain ranges. Further, it is claimed that the underlying model is based on influence percolation and a martingale condition. This paper examines these claims and their validity for capturing large price falls in the Hang Seng stock market index over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these 11 crashes. Interestingly, the LPPL fit could have predicted the substantial fall in the Hang Seng index during the recent global downturn. Overall, the mechanism posited as underlying the LPPL model does not do so, and the data used to support the fit of the LPPL model to bubbles does so only partially. © 2013.

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This work has concentrated on the testing of induction machines to determine their temperature rise at full-load without mechanically coupling to a load machine. The achievements of this work are outlined as follows. 1. Four distinct categories of mixed-frequency test using an inverter have been identified by the author. The simulation results of these tests as well as the conventional 2-supply test have been analysed in detail. 2. Experimental work on mixed-frequency tests has been done on a small (4 kW) squirrel cage induction machine using a voltage source PWM inverter. Two out of the four categories of test suggested have been tested and the temperature rise results were found to be similar to the results of a direct loading test. Further, one of the categories of test proposed has been performed on a 3.3 kW slip-ring induction machine for the conformation of the rotor values. 3. A low current supply mixed-frequency test-rig has been proposed. For this purpose, a resonant bank was connected to the DC link of the inverter in order to maintain the exchange of power between the test machine and the resonant bank instead of between the main supply and the test machine. The resonant bank was then replaced with a special electro-mechanical energy storage unit. The current of the main power supply was then reduced in amplitude. 4. A variable inertia test for full load temperature rise testing of induction machines has been introduced. This test is purely mechanical in nature and does not require any electrical connection of the test machine to any other machine. It has the advantage of drawing very little net power from the supply.

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A negative input-resistance compensator is designed to stabilize a power electronic brushless dc motor drive with constant power-load characteristics. The strategy is to feed a portion of the changes in the dc-link voltage into the current control loop to modify the system input impedance in the midfrequency range and thereby to damp the input filter. The design process of the compensator and the selection of parameters are described. The impact of the compensator is examined on the motor-controller performance, and finally, the effectiveness of the controller is verified by simulation and experimental testing.

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We report on high power issues related to the reliability of fibre Bragg gratings inscribed with an infrared femtosecond laser using the point-by-point writing method. Conventionally, fibre Bragg gratings have usually been written in fibres using ultraviolet light, either holographically or using a phase mask. Since the coating is highly absorbing in the UV, this process normally requires that the protective polymer coating is stripped prior to inscription, with the fibre then being recoated. This results in a time consuming fabrication process that, unless great care is taken, can lead to fibre strength degradation, due to the presence of surface damage. The recent development of FBG inscription using NIR femtosecond lasers has eliminated the requirement for the stripping of the coating. At the same time the ability to write gratings point-by-point offers the potential for great flexibility in the grating design. There is, however, a requirement for reliability testing of these gratings, particularly for use in telecommunications systems where high powers are increasingly being used in long-haul transmission systems making use of Raman amplification. We report on a study of such gratings which has revealed the presence of broad spectrum power losses. When high powers are used, even at wavelengths far removed from the Bragg condition, these losses produce an increase in the fibre temperature due to absorption in the coating. We have monitored this temperature rise using the wavelength shift in the grating itself. At power levels of a few watts, various temperature increases were experienced ranging from a few degrees up to the point where the buffer completely melts off the fibre at the grating site. Further investigations are currently under way to study the optical loss mechanisms in order to optimise the inscription mechanism and minimise such losses.

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To examine the detailed operation of the power distribution network in a future more electric aircraft that employs electric actuation systems, a Micro-Cap SPICE simulation is developed for one of the essential buses. Particular attention is paid to model accurately the most important effects that influence system power quality. Representative system and flight data are used to illustrate the operation of the simulation and to assess the power quality conditions within the network as the flight control surfaces are deployed. The results illustrate the importance of correct cable sizing to ensure stable operation of actuators during transient conditions.

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Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

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Tunable Raman fiber lasers have attracted great interest owing to their high efficiency and reliability important for applications, such as optical fiber communications and sensing, spectroscopy, and instrument testing. Their tuning range is defined by the Raman gain bandwidth amounting to about 40 nm in telecom spectral range (∼1550 nm) for conventional silica single mode fibers (SMF). To increase the range, highly nonlinear fibers which broaden pump spectrum may be incorporated in the cavity of Raman fiber lasers, see e.g. [1]. Another approach is to involve Rayleigh scattering forming random distributed feedback in a relatively long fiber resulting in prominent flattening of the tuning curve [2]. In this paper we report on combination of these two techniques in tunable Raman fiber lasers thus providing great improvement of their output characteristics. © 2013 IEEE.

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Since wind has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safety and economics of wind energy utilization. In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. Firstly the wind speed data from NWP was corrected by a GP. Then, as there is always a defined limit on power generated in a wind turbine due the turbine controlling strategy, a Censored GP was used to model the relationship between the corrected wind speed and power output. To validate the proposed approach, two real world datasets were used for model construction and testing. The simulation results were compared with the persistence method and Artificial Neural Networks (ANNs); the proposed model achieves about 11% improvement in forecasting accuracy (Mean Absolute Error) compared to the ANN model on one dataset, and nearly 5% improvement on another.

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The PMSG-based wind power generation system protection is presented in this paper. For large-scale systems, a voltagesource converter rectifier is included. Protection circuits for this topology are studied with simulation results for cable permanent fault conditions. These electrical protection methods are all in terms of dumping redundant energy resulting from disrupted path of power delivery. Pitch control of large-scale wind turbines are considered for effectively reducing rotor shaft overspeed. Detailed analysis and calculation of damping power and resistances are presented. Simulation results including fault overcurrent, DC-link overvoltage and wind turbine overspeed are shown to illustrate the system responses under different protection schemes to compare their application and effectiveness.