867 resultados para measurement and metrology


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Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

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Manipulator motion planning is a classic problem in robotics, with a number of complete solutions available for their motion in controlled (industrial) environments. Owing to recent technological advances in the field of robotics, there has been a significant development of more complex robots with high-fidelity sensors and more computational power. One such example has been a rise in the production of humanoid robots equipped with dual-arm manipulators which require complex motion planning algorithms. Also, the technological advances have resulted in a shift from using manipulators in strictly controlled environments, to investigating the deployment of manipulators in dynamic or unknown environments. As a result, a greater emphasis has been put on the development of local motion planners, which can provide real-time solutions to these problems. Artificial Potential Fields (APFs) is one such popular local motion planning technique, which can be applied to manipulator motion planning, however, the basic algorithm is severely prone to local minima problems. Here, two modified APF-based strategies for solving the dual-arm motion planning task in unknown environments are proposed. Both techniques make use of configuration sampling and subgoal selection to assist the APFs in avoiding these local minima scenarios. Extensive simulation results are presented to validate the efficacy of the proposed methodology.

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Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in certain harsh environments, for example, in combustion systems and engine exhausts, large wire diameters are required, and consequently the measurement bandwidth is reduced. This article discusses a software compensation technique to address the loss of high frequency fluctuations based on measurements from two thermocouples. In particular, a difference equation (DE) approach is proposed and compared with existing methods both in simulation and on experimental test rig data with constant flow velocity. It is found that the DE algorithm, combined with the use of generalized total least squares for parameter identification, provides better performance in terms of time constant estimation without any a priori assumption on the time constant ratios of the thermocouples.

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Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stu¨dli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.

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This letter presents the design of a thin microwave absorber which exhibits a -10 dB reflectivity bandwidth of 108% at normal incidence and 16% for simultaneous suppression of TE and TM polarised waves over the angular range 0-45° is presented. The structure consists of a 3 mm-thick metal backed frequency selective surface (FSS) with four resistively loaded hexagonal loop elements in each unit cell. The surface resistivity and width of the loops are carefully chosen to maximise the bandwidth by merging the reflection nulls that are generated by the multi-resonant absorber. Measurement and simulation results are in good agreement over the broad frequency range 7.8-24 GHz.

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This paper presents an electrochemical instrumentation system capable of real-time in situ detection of heavy metals. A practical approach to introduce acidity compensation against changes in amplitude of the peak currents is also presented. The compensated amplitudes can then be used to predict the concentration level of heavy metals. The system uses differential pulse anodic stripping voltammetry, which is a precise and sensitive analytical method with excellent limits of detection. The instrument is capable of detecting lead, cadmium, zinc, nickel and copper with good sensitivity and precision. The system avoids expensive and time-consuming procedures and may be used in a variety of situations to help environmental assessment and control. 

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The aim of this paper is to develop a new extruder control system for recycled materials which has ability to automatically maintain constant a polymer melt viscosity of mixed recycled polymers during extrusion, regardless of variations in the Melt Flow Index (MFI) of recycled mixed grade high density polyethylene (HDPE) feedstock. A closed-loop controller is developed to automatically regulate screw speed and barrel temperature profile to achieve constant viscosity and enable consistent processing of variable grade recycled HDPE materials. The experimental results of real time viscosity measurement and control using a 38mm single screw extruder with different recycled HDPEs with widely different MFIs are reported in this work

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A novel digital image correlation (DIC) technique has been developed to track changes in textile yarn orientations during shear characterisation experiments, requiring only low-cost digital imaging equipment. Fabric shear angles and effective yarn strains are calculated and visualised using this new DIC technique for bias extension testing of an aerospace grade, carbon-fibre reinforcement material with a plain weave architecture. The DIC results are validated by direct measurement, and the use of a wide bias extension sample is evaluated against a more commonly used narrow sample. Wide samples exhibit a shear angle range 25% greater than narrow samples and peak loads which are 10 times higher. This is primarily due to excessive yarn slippage in the narrow samples; hence, the wide sample configuration is recommended for characterisation of shear properties which are required for accurate modelling of textile draping.

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Rapid in situ diagnosis of damage is a key issue in the preservation of stone-built cultural heritage. This is evident in the increasing number of congresses, workshops and publications dealing with this issue. With this increased activity has come, however, the realisation that for many culturally significant artefacts it is not possible either to remove samples for analysis or to affix surface markers for measurement. It is for this reason that there has been a growth of interest in non-destructive and minimally invasive techniques for characterising internal and external stone condition. With this interest has come the realisation that no single technique can adequately encompass the wide variety of parameters to be assessed or provide the range of information required to identify appropriate conservation. In this paper we describe a strategy to address these problems through the development of an integrated `tool kit' of measurement and analytical techniques aimed specifically at linking object-specific research to appropriate intervention. The strategy is based initially upon the acquisition of accurate three-dimensional models of stone-built heritage at different scales using a combination of millimetre accurate LiDAR and sub-millimetre accurate Object Scanning that can be exported into a GIS or directly into CAD. These are currently used to overlay information on stone characteristics obtained through a combination of Ground Penetrating Radar, Surface Permeametry, Colorimetry and X-ray Fluorescence, but the possibility exists for adding to this array of techniques as appropriate. In addition to the integrated three-dimensional data array provided by superimposition upon Digital Terrain Models, there is the capability of accurate re-measurement to show patterns of surface loss and changes in material condition over time. Thus it is possible to both record and base-line condition and to identify areas that require either preventive maintenance or more significant pre-emptive intervention. In pursuit of these goals the authors are developing, through a UK Government supported collaboration between University Researchers and Conservation Architects, commercially viable protocols for damage diagnosis, condition monitoring and eventually mechanisms for prioritizing repairs to stone-built heritage. The understanding is, however, that such strategies are not age-constrained and can ultimately be applied to structures of any age.

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This paper is concerned with the analysis of the stability of delayed recurrent neural networks. In contrast to the widely used Lyapunov–Krasovskii functional approach, a new method is developed within the integral quadratic constraints framework. To achieve this, several lemmas are first given to propose integral quadratic separators to characterize the original delayed neural network. With these, the network is then reformulated as a special form of feedback-interconnected system by choosing proper integral quadratic constraints. Finally, new stability criteria are established based on the proposed approach. Numerical examples are given to illustrate the effectiveness of the new approach.

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This paper introduces a novel load sharing algorithm to enable island synchronization. The system model used for development is based on an actual system for which historical measurement and fault data is available and is used to refine and test the algorithms performance and validity. The electrical system modelled is selected due to its high-level of hydroelectric generation and its history of islanding events. The process of developing the load sharing algorithm includes a number of steps. Firstly, the development of a simulation model to represent the case study accurately - this is validated by way of matching system behavior based on data from historical island events. Next, a generic island simulation is used to develop the load sharing algorithm. The algorithm is then tested against the validated simulation model representing the case study area selected. Finally, a laboratory setup is described which is used as validation method for the novel load sharing algorithm.

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Rationale: IL-17A is purported to help drive early pathogenesis in acute respiratory distress syndrome (ARDS) by enhancing neutrophil recruitment. Whilst IL-17A is the archetypal cytokine of T helper (Th)17 cells, it is produced by a number of lymphocytes, the source during ARDS being unknown.

Objectives: To identify the cellular source and the role of IL17A in the early phase of lung injury

Methods: Lung injury was induced in WT (C57BL/6) and IL-17 KO mice with aerosolised LPS (100 µg) or Pseudomonas aeruginosa infection. Detailed phenotyping of the cells expressing RORγt, the transcriptional regulator of IL-17 production, in the mouse lung at 24 hours was carried out by flow cytometry.

Measurement and Main Results: A 100-fold reduction in neutrophil infiltration was observed in the lungs of the IL-17A KO compared to wild type (WT) mice. The majority of RORγt+ cells in the mouse lung were the recently identified type 3 innate lymphoid cells (ILC3). Detailed characterisation revealed these pulmonary ILC3s (pILC3s) to be discrete from those described in the gut. The critical role of these cells was verified by inducing injury in Rag2 KO mice which lack T cells but retain ILCs. No amelioration of pathology was observed in the Rag2 KO mice.

Conclusions: IL-17 is rapidly produced during lung injury and significantly contributes to early immunopathogenesis. This is orchestrated largely by a distinct population of pILC3 cells. Modulation of pILC3s’ activity may potentiate early control of the inflammatory dysregulation seen in ARDS, opening up new therapeutic targets.

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A novel type of microwave probes based on the loaded aperture geometry has been proposed and experimentally evaluated for dielectrics characterisation and high-resolution near-field imaging. Experimental results demonstrate the possibility of very accurate microwave spectroscopic characterisation of thin lossy dielectric samples and biological materials containing water. High-resolution images of the subwavelength lossy dielectric strips and wet and dry leaves have been obtained with amplitude contrast around 10-20 dB and spatial resolution better than one-tenth of a wavelength in the near-field zone. A microwave imaging scenario for the early-stage skin cancer identification based on the artificial dielectric model has also been explored. This model study shows that the typical resolution of an artificial malignant tumour with a characteristic size of one-tenth of a wavelength can be discriminated with at least 6 dB amplitude and 50° phase contrast from the artificial healthy skin and with more than 3 dB contrast from a benign lesion of the same size. It has also been demonstrated that the proposed device can efficiently deliver microwave energy to very small, subwavelength, focal areas which is highly sought in the microwave hyperthermia applications.

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Double photoionization accompanied by loss of n C atoms (n=0, 2, 4, 6) was investigated by merging beams of Xe@C60+ ions and synchrotron radiation and measuring the yields of product ions. The giant 4d dipole resonance of the caged Xe atom has a prominent signature in the cross section for these product channels, which together account for 6.2 ± 1.4 of the total Xe 4d oscillator strength of 10. Compared to that for a free Xe atom, the oscillator strength is redistributed in photon energy due to multipath interference of outgoing Xe 4d photoelectron waves that may be transmitted or reflected by the spherical C60+ molecular cage, yielding so-called confinement resonances. The data are compared with an earlier measurement and with theoretical predictions for this single-molecule photoelectron interferometer system. Relativistic R-matrix calculations for the Xe atom in a spherical potential shell representing the fullerene cage show the sensitivity of the interference pattern to the molecular geometry. © 2013 American Physical Society.