75 resultados para Variable Parameters Control Charts

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


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Recently, considerable efforts have been made in the attempt to map quick clay areas using electrical resistivity measurements. However there is a lack of understanding regarding which soil parameters control the measured resistivity values. To address this issue, inverted resistivity values from 15 marine clay sites in Norway have been compared with basic geotechnical index properties. It was found that the resistivity value is strongly controlled by the salt content of the pore fluid. Resistivity decreases rapidly with increasing salt content. There is also a relatively clear trend of decreasing resistivity with increasing clay content and plasticity index. Resistivity values become very low (˜5 O·m) for high clay content (>50%), medium- to high-plasticity (Ip ˜ 20%) materials with salt content values greater than about 8 g/L (or corresponding remoulded shear strength values greater than 4 kPa). For the range of values studied, there is poor correlation between resistivity and bulk density and between resistivity and water content. The data studied suggest that the range of resistivity values corresponding to quick clay is 10 to 100 O·m, which is consistent with other published limits. A comparison is made between two-dimensional electrical resistivity tomography (ERT) and resistivity cone penetration test (RCPTU) data for two of the sites and the two sets of data show similar trends and values irrespective of scale effect.

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This is the first paper that shows and theoretically analyses that the presence of auto-correlation can produce considerable alterations in the Type I and Type II errors in univariate and multivariate statistical control charts. To remove this undesired effect, linear inverse ARMA filter are employed and the application studies in this paper show that false alarms (increased Type I errors) and an insensitive monitoring statistics (increased Type II errors) were eliminated.

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Energies of the 700 lowest levels in Fe XX have been obtained using the multiconfiguration Dirac-Fock method. Configuration interaction method on the basis set of transformed radial orbitals with variable parameters taking into account relativistic corrections in the Breit-Pauli approximation was used to crosscheck our presented results. Transition probabilities, oscillator and line strengths are presented for electric dipole (E1), electric quadrupole (E2) and magnetic dipole (M1) transitions among these levels. The total radiative transition probabilities from each level are also provided. Results are compared with data compiled by NIST and with other theoretical work.

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In many situations, the number of data points is fixed, and the asymptotic convergence results of popular model selection tools may not be useful. A new algorithm for model selection, RIVAL (removing irrelevant variables amidst Lasso iterations), is presented and shown to be particularly effective for a large but fixed number of data points. The algorithm is motivated by an application of nuclear material detection where all unknown parameters are to be non-negative. Thus, positive Lasso and its variants are analyzed. Then, RIVAL is proposed and is shown to have some desirable properties, namely the number of data points needed to have convergence is smaller than existing methods.

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Glycosylation of low density lipoproteins obtained from 16 patients with Type 1 (insulin-dependent) diabetes and from 16 age-, sex-, and race-matched controls, was determined. The diabetic patients were normolipaemic and were in good or fair glycaemic control. Eleven patients performed home blood glucose monitoring. Glycosylation of low density lipoproteins in the diabetic patients was significantly higher (p less than 0.001) than in the control subjects, and was significantly correlated with haemoglobin A1c, (p less than 0.01), glycosylation of plasma proteins, (p less than 0.001), and mean home blood glucose, (p less than 0.01). This study confirms that, in diabetic patients, increased glycosylation of low density lipoprotein occurs to an extent which correlates closely with other commonly used indices of glycaemic control.

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This paper studies the system modelling and control aspects of switched reluctance generator (SRG) based variable speed wind turbines. A control system is implemented to provide proper operation of the SRG as well as power tracking capabilities for varying wind speeds. The control system for the grid side inverter that will allow the SRG to properly generate power to the system is also presented. Studies are presented of both the SRG and inverter control systems capabilities during a balanced three-phase fault. The paper will demonstrate that the SRG based wind turbine presents a feasible variable wind speed solution with good fault response capabilities.

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Thermoforming processes generally employ sheet temperature monitoring as the primary means of process control. In this paper the development of an alternative system that monitors plug force is described. Tests using a prototype device have shown that the force record over a forming cycle creates a unique map of the process operation. Key process features such as the sheet modulus, sheet sag and the timing of the process stages may be readily observed, and the effects of changes in all of the major processing parameters are easily distinguished. Continuous, cycle-to-cycle tests show that the output is consistent and repeatable over a longer time frame, providing the opportunity for development of an on-line process control system. Further testing of the system is proposed.

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This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.

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The present paper describes the results of an investigation into the modelling of plug assisted thermoforming. The objective of this work was to improve the finite element modelling of thermoforming through an enhanced understanding of the physical elements underlying the process. Experiments were carried out to measure the effects on output of changes in major parameters and simultaneously simple finite element models were constructed. The experimental results show that the process creates conflicting and interrelated contact friction and heat transfer effects that largely dictate the final wall thickness distribution. From the simulation work it was demonstrated that a high coefficient of friction and no heat transfer can give a good approximation of the actual wall thickness distribution. However, when conduction was added to the model the results for lower friction values were greatly improved. It was concluded that further work is necessary to provide realistic measurements and models for contact effects in thermoforming.

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Atmospheric parameters and surface chemical compositions are presented for eight stars, classified as B1 or B2 but with a range of luminosity classes, in the northern double cluster h and chi Persei. Echelle spectroscopy (covering the wavelength region 3900 to 4700 Ä) and grating spectroscopy (of the Balmer, H? and Hß lines) were analysed using non-LTE synthetic spectra based on LTE line-blanketed atmosphere structures. High microturbulences are found in our sample, and this quantity must be included in the computation of the non-LTE level populations; its effect is generally to decrease the derived metal abundances by typically 0.1 dex but by up to 0.4 dex. Our absolute abundances are in reasonable agreement with those previously found for main sequence B-type stars, while we find some evidence for small abundance variations (particularly for nitrogen) within our sample. One star (BD+56 678) appears to be a spectrum variable and at two epochs shows a highly enriched nitrogen spectrum. Our atmospheric parameters imply that two stars have previously been mis-identified as main sequence objects and a distance modulus, at the higher end of the values previously deduced. The observational HR diagram is consistent with stellar evolutionary models that explicitly include the effects of rotation.

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The dynamics of high energetic electrons (>= 11.7 eV) in a modified industrial confined dual-frequency capacitively coupled RF discharge (Exelan, Lam Research Inc.), operated at 1.937 MHz and 27.118 MHz, is investigated by means of phase resolved optical emission spectroscopy. Operating in a He-O-2. plasma with small rare gas admixtures the emission is measured, with one-dimensional spatial resolution along the discharge axis. Both the low and high frequency RF cycle are resolved. The diagnostic is based on time dependent measurements of the population densities of specifically chosen excited rare gas states. A time dependent model, based on rate equations, describes the dynamics of the population densities of these levels. Based on this model and the comparison of the excitation of various rare gas states, with different excitation thresholds, time and space resolved electron temperature, propagation velocity and qualitative electron density as well as electron energy distribution functions are determined. This information leads to a better understanding of the dual-frequency sheath dynamics and shows, that separate control of ion energy and electron density is limited.

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This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.