41 resultados para Measurement system

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The mean velocity and turbulence intensity are the two main inputs to investigate the ship propeller induced seabed scouring resulting from a vessel is manoeuvring within a port where the underkeel clearances are low. More accurate data including the turbulence intensity is now available by using the laser doppler anemometry (LDA) measurement system and computational fluid dynamics (CFD) approach. Turbulence intensity has a loose definition, which is the velocity fluctuation as the root mean square (RMS) referenced to a mean flow velocity. However, the velocity fluctuation and mean velocity can be the overall value includingxy and z directions or the value of a single component. LDA and CFD results were obtained from two different acquisition systems (Dantec LDA system and Fluent CFD package) and therefore the outputs cannot be compared directly. An effective method is proposed for comparing the turbulence intensity between the experimental measurements and the computational predictions within a ship propeller jet. The flow patterns of turbulence intensity within a ship propeller jet are presented by using the LDA measurements and CFD results from turbulence models of standard k-e, RNG k-e, realizable ke, standard k?, SST k?and Reynolds stresses.

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The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

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Anti-islanding protection is becoming increasingly important due to the rapid installation of distributed generation from renewable resources like wind, tidal and wave, solar PV, bio-fuels, as well as from other resources like diesel. Unintentional islanding presents a potential risk for damaging utility plants and equipment connected from the demand side, as well as to public and personnel in utility plants. This paper investigates automatic islanding detection. This is achieved by deploying a statistical process control approach for fault detection with the real-time data acquired through a wide area measurement system, which is based on Phasor Measurement Unit (PMU) technology. In particular, the principal component analysis (PCA) is used to project the data into principal component subspace and residual space, and two statistics are used to detect the occurrence of fault. Then a fault reconstruction method is used to identify the fault and its development over time. The proposed scheme has been used in a real system and the results have confirmed that the proposed method can correctly identify the fault and islanding site.

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This paper investigates the potential for using the windowed variance of the received signal strength to select from a set of predetermined channel models for a wireless ranging or localization system. An 868 MHz based measurement system was used to characterize the received signal strength (RSS) of the off-body link formed between two wireless nodes attached to either side of a human thorax and six base stations situated in the local surroundings.

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An experimental investigation of the argon plasma behavior near the E-H transition in an inductively coupled Gaseous Electronics Conference reference cell is reported. Electron density and temperature, ion density, argon metastable density, and optical emission measurements have been made as function of input power and gas pressure. When plotted versus plasma power, applied power corrected for coil and hardware losses, no hysteresis is observed in the measured plasma parameter dependence at the E-H mode transition. This suggests that hysteresis in the E-H mode transition is due to ignoring inherent power loss, primarily in the matching system.

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The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

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This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

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The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

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Loss-of-mains protection is an important component of the protection systems of embedded generation. The role of loss-of-mains is to disconnect the embedded generator from the utility grid in the event that connection to utility dispatched generation is lost. This is necessary for a number of reasons, including the safety of personnel during fault restoration and the protection of plant against out-of-synchronism reclosure to the mains supply. The incumbent methods of loss-of-mains protection were designed when the installed capacity of embedded generation was low, and known problems with nuisance tripping of the devices were considered acceptable because of the insignificant consequence to system operation. With the dramatic increase in the installed capacity of embedded generation over the last decade, the limitations of current islanding detection methods are no longer acceptable. This study describes a new method of loss-of-mains protection based on phasor measurement unit (PMU) technology, specifically using a low cost PMU device of the authors' design which has been developed for distribution network applications. The proposed method addresses the limitations of the incumbent methods, providing a solution that is free of nuisance tripping and has a zero non-detection zone. This system has been tested experimentally and is shown to be practical, feasible and effective. Threshold settings for the new method are recommended based on data acquired from both the Great Britain and Ireland power systems.

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This paper presents a new method for online determination of the Thèvenin equivalent parameters of a power system at a given node using the local PMU measurements at that node. The method takes into account the measurement errors and the changes in the system side. An analysis of the effects of changes in system side is carried out on a simple two-bus system to gain an insight of the effect of system side changes on the estimated Thévenin equivalent parameters. The proposed method uses voltage and current magnitudes as well as active and reactive powers; thus avoiding the effect of phase angle drift of the PMU and the need to synchronize measurements at different instances to the same reference. Applying the method to the IEEE 30-bus test system has shown its ability to correctly determine the Thévenin equivalent even in the presence of measurement errors and/or system side changes.

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Although the NO removal-based air-purification ISO method ISO 22197-1:2007 is well established, its preconditioning requirements mean that only the initial activity of the photocatalyst under test is measured owing to the often-reported, gradual alteration of the surface kinetics for NO oxidation by air through the accumulation of surface HNO3. Herein, we compare the photocatalytic NO removal abilities of a number of different, common TiO2 materials, surface-saturated with photogenerated HNO3, with their behaviours observed during the typical 5 h-long ISO standard test. It is found that all the TiO2 materials studied eventually become largely NO to NO2 converters after sufficient exposure to NO under irradiation (>5 h) due to the accumulation of surface HNO3. The UV exposure time, t*, necessary to reach this HNO3 saturated condition is different for each different catalyst. As a consequence, an alternative preconditioning process for the ISO method is proposed which can be used to provide a more realistic measure of the photocatalytic activity of the underlying material and provide a measure of the NOx removing capacity of the photocatalytic material under test.

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With the main focus on safety, design of structures for vibration serviceability is often overlooked or mismanaged, resulting in some high profile structures failing publicly to perform adequately under human dynamic loading due to walking, running or jumping. A standard tool to inform better design, prove fitness for purpose before entering service and design retrofits is modal testing, a procedure that typically involves acceleration measurements using an array of wired sensors and force generation using a mechanical shaker. A critical but often overlooked aspect is using input (force) to output (response) relationships to enable estimation of modal mass, which is a key parameter directly controlling vibration levels in service.

This paper describes the use of wireless inertial measurement units (IMUs), designed for biomechanics motion capture applications, for the modal testing of a 109 m footbridge. IMUs were first used for an output-only vibration survey to identify mode frequencies, shapes and damping ratios, then for simultaneous measurement of body accelerations of a human subject jumping to excite specific vibrations modes and build up bridge deck accelerations at the jumping location. Using the mode shapes and the vertical acceleration data from a suitable body landmark scaled by body mass, thus providing jumping force data, it was possible to create frequency response functions and estimate modal masses.

The modal mass estimates for this bridge were checked against estimates obtained using an instrumented hammer and known mass distributions, showing consistency among the experimental estimates. Finally, the method was used in an applied research application on a short span footbridge where the benefits of logistical and operational simplicity afforded by the highly portable and easy to use IMUs proved extremely useful for an efficient evaluation of vibration serviceability, including estimation of modal masses.

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A new approach to the search for residues of unknown growth promoting agents such as anabolic steroids and -agonists in feed is presented. Following primary extraction and clean-up, samples are separated using gradient liquid chromatography (LC). The effluent is split towards two identical 96-well fraction collectors and an optional electrospray quadrupole time-of-flight mass spectrometry (QTOFMS) system for accurate mass measurement. One 96-well plate is used for a bioassay (enzyme-immuno assay, receptor assay) and will detect the bioactivity and position of the relevant peak in the chromatogram. The positive well in the second 96-well plate is used for identification by LC/QTOFMS/MS. The value of this LC/bioassay/QTOFMS/MS methodology is highlighted by the finding and structure elucidation of a new -agonist in a feed extract.

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For the purpose of a nonlocality test, we propose a general correlation observable of two parties by utilizing local d- outcome measurements with SU(d) transformations and classical communications. Generic symmetries of the SU(d) transformations and correlation observables are found for the test of nonlocality. It is shown that these symmetries dramatically reduce the number of numerical variables, which is important for numerical analysis of nonlocality. A linear combination of the correlation observables, which is reduced to the Clauser- Home-Shimony-Holt (CHSH) Bell's inequality for two outcome measurements, leads to the Collins-Gisin-Linden-Massar-Popescu (CGLMP) nonlocality test for d-outcome measurement. As a system to be tested for its nonlocality, we investigate a continuous- variable (CV) entangled state with d measurement outcomes. It allows the comparison of nonlocality based on different numbers of measurement outcomes on one physical system. In our example of the CV state, we find that a pure entangled state of any degree violates Bell's inequality for d(greater than or equal to2) measurement outcomes when the observables are of SU(d) transformations.