927 resultados para Process monitoring
Resumo:
Melt viscosity is a key indicator of product quality in polymer extrusion processes. However, real time monitoring and control of viscosity is difficult to achieve. In this article, a novel “soft sensor” approach based on dynamic gray-box modeling is proposed. The soft sensor involves a nonlinear finite impulse response model with adaptable linear parameters for real-time prediction of the melt viscosity based on the process inputs; the model output is then used as an input of a model with a simple-fixed structure to predict the barrel pressure which can be measured online. Finally, the predicted pressure is compared to the measured value and the corresponding error is used as a feedback signal to correct the viscosity estimate. This novel feedback structure enables the online adaptability of the viscosity model in response to modeling errors and disturbances, hence producing a reliable viscosity estimate. The experimental results on different material/die/extruder confirm the effectiveness of the proposed “soft sensor” method based on dynamic gray-box modeling for real-time monitoring and control of polymer extrusion processes. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers
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Over the last 5–10 years, marine spatial planning (MSP) has emerged as a new management regime for national and international waters and has already attracted a substantial body of multi-disciplinary research on its goals and policy processes. This paper argues that this literature has generally lacked deeper reflexive engagement with the emerging system of governance for our seas that has meant that many of MSP’s core concepts, assumptions and institutional arrangements have not been subject rigorous intellectual debate. In an attempt to initiate such an approach, this article explores the relationship between MSP and its land-based cousin, terrestrial spatial planning (TSP). While it is recognized that there are inherent limitations to a comparison of these two systems, it is argued that the tradition of social science debate over the purpose and processes of TSP can be used as a useful stimulus for a more rigorous reflection of such issues as they relate to MSP. The article therefore explores some of the parallels between MSP and TSP and then discusses some of the key intellectual traditions that have shaped TSP and the implications these may have for future marine planning practice. The article concludes with a number of potentially useful new avenues that may form the basis of a critical research agenda for MSP.
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This paper presents an innovative sensor system, created specifically for new civil engineering structural monitoring applications, allowing specially packaged fiber grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement with full temperature compensation. The sensor consists of two fiber Bragg gratings that are protected within a polypropylene package, with one of the fiber gratings isolated from the influence of strain and thus responding only to temperature variations, while the other is sensitive to both strain and temperature. To achieve this, the temperature-monitoring fiber grating is slightly bent and enclosed in a metal envelope to isolate it effectively from the strain. Through an appropriate calibration process, both the strain and temperature coefficients of each individual grating component when incorporated in the sensor system can be thus obtained. By using these calibrated coefficients in the operation of the sensor, both strain and temperature can be accurately determined. The specific application for which these sensors have been designed is seen when installed on an innovative small-scale flexi-arch bridge where they are used for real-time strain measurements during the critical installation stage (lifting) and loading. These sensors have demonstrated enhanced resilience when embedded in or surface-mounted on such concrete structures, providing accurate and consistent strain measurements not only during installation but subsequently during use. This offers an inexpensive and highly effective monitoring system tailored for the new, rapid method of the installation of small-scale bridges for a variety of civil engineering applications.
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Weathering of stone is one of the major reasons for the damage of stone masonry structures and it takes place due to interlinked chemical, physical and biological processes in stones. The key parameters involved in the deterioration processes are temperature, moisture and salt. It is now known that the sudden variations in temperature and moisture greatly accelerate the weathering process of the building stone fabric. Therefore, in order to monitor these sudden variations an effective and continuous monitoring system is needed. Furthermore, it must consist of robust sensors which are accurate and can survive in the harsh environments experienced in and around masonry structures. Although salt penetration is important for the rate of deterioration of stone masonry structures, the processes involved are much slower than the damage associated with temperature and moisture variations. Therefore, in this paper a novel fibre optic temperature cum relative humidity sensor is described and its applicability in monitoring building stones demonstrated. The performance of the sensor is assessed in an experiment comprising wetting and drying of limestone blocks. The results indicate that the novel fibre optic relative humidity sensor which is tailor made for applications in masonry structures performed well in wetting and drying tests, whilst commercial capacitance based sensors failed to recover during the drying regime for a long period after a wetting regime. That is, the fibre optic sensor has the capability to measure both sorption and de-sorption characteristics of stone blocks. This sensor is used in a test wall in Oxford and the data thus obtained strengthened the laboratory observations.
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Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.
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Topic
To compare the accuracy of optical coherence tomography (OCT) with alternative tests for monitoring neovascular age-related macular degeneration (nAMD) and detecting disease activity among eyes previously treated for this condition.
Clinical RelevanceTraditionally, fundus fluorescein angiography (FFA) has been considered the reference standard to detect nAMD activity, but FFA is costly and invasive. Replacement of FFA by OCT can be justified if there is a substantial agreement between tests.
MethodsSystematic review and meta-analysis. The index test was OCT. The comparator tests were visual acuity, clinical evaluation (slit lamp), Amsler chart, color fundus photographs, infrared reflectance, red-free images and blue reflectance, fundus autofluorescence imaging, indocyanine green angiography (ICGA), preferential hyperacuity perimetry, and microperimetry. We searched the following databases: MEDLINE, MEDLINE In-Process, EMBASE, Biosis, Science Citation Index, the Cochrane Library, Database of Abstracts of Reviews of Effects, MEDION, and the Health Technology Assessment database. The last literature search was conducted in March 2013. We used the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) to assess risk of bias.
ResultsWe included 8 studies involving more than 400 participants. Seven reported the performance of OCT (3 time-domain [TD] OCT, 3 spectral-domain [SD] OCT, 1 both types) and 1 reported the performance of ICGA in the detection of nAMD activity. We did not find studies directly comparing tests in the same population. The pooled sensitivity and specificity of TD OCT and SD OCT for detecting active nAMD was 85% (95% confidence interval [CI], 72%–93%) and 48% (95% CI, 30%–67%), respectively. One study reported ICGA with sensitivity of 75.9% and specificity of 88.0% for the detection of active nAMD. Half of the studies were considered to have a high risk of bias.
ConclusionsThere is substantial disagreement between OCT and FFA findings in detecting active disease in patients with nAMD who are being monitored. Both methods may be needed to monitor patients comprehensively with nAMD.
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BACKGROUND: Age-related macular degeneration is the most common cause of sight impairment in the UK. In neovascular age-related macular degeneration (nAMD), vision worsens rapidly (over weeks) due to abnormal blood vessels developing that leak fluid and blood at the macula.
OBJECTIVES: To determine the optimal role of optical coherence tomography (OCT) in diagnosing people newly presenting with suspected nAMD and monitoring those previously diagnosed with the disease.
DATA SOURCES: Databases searched: MEDLINE (1946 to March 2013), MEDLINE In-Process & Other Non-Indexed Citations (March 2013), EMBASE (1988 to March 2013), Biosciences Information Service (1995 to March 2013), Science Citation Index (1995 to March 2013), The Cochrane Library (Issue 2 2013), Database of Abstracts of Reviews of Effects (inception to March 2013), Medion (inception to March 2013), Health Technology Assessment database (inception to March 2013).
REVIEW METHODS: Types of studies: direct/indirect studies reporting diagnostic outcomes.
INDEX TEST: time domain optical coherence tomography (TD-OCT) or spectral domain optical coherence tomography (SD-OCT).
COMPARATORS: clinical evaluation, visual acuity, Amsler grid, colour fundus photographs, infrared reflectance, red-free images/blue reflectance, fundus autofluorescence imaging, indocyanine green angiography, preferential hyperacuity perimetry, microperimetry. Reference standard: fundus fluorescein angiography (FFA). Risk of bias was assessed using quality assessment of diagnostic accuracy studies, version 2. Meta-analysis models were fitted using hierarchical summary receiver operating characteristic curves. A Markov model was developed (65-year-old cohort, nAMD prevalence 70%), with nine strategies for diagnosis and/or monitoring, and cost-utility analysis conducted. NHS and Personal Social Services perspective was adopted. Costs (2011/12 prices) and quality-adjusted life-years (QALYs) were discounted (3.5%). Deterministic and probabilistic sensitivity analyses were performed.
RESULTS: In pooled estimates of diagnostic studies (all TD-OCT), sensitivity and specificity [95% confidence interval (CI)] was 88% (46% to 98%) and 78% (64% to 88%) respectively. For monitoring, the pooled sensitivity and specificity (95% CI) was 85% (72% to 93%) and 48% (30% to 67%) respectively. The FFA for diagnosis and nurse-technician-led monitoring strategy had the lowest cost (£39,769; QALYs 10.473) and dominated all others except FFA for diagnosis and ophthalmologist-led monitoring (£44,649; QALYs 10.575; incremental cost-effectiveness ratio £47,768). The least costly strategy had a 46.4% probability of being cost-effective at £30,000 willingness-to-pay threshold.
LIMITATIONS: Very few studies provided sufficient information for inclusion in meta-analyses. Only a few studies reported other tests; for some tests no studies were identified. The modelling was hampered by a lack of data on the diagnostic accuracy of strategies involving several tests.
CONCLUSIONS: Based on a small body of evidence of variable quality, OCT had high sensitivity and moderate specificity for diagnosis, and relatively high sensitivity but low specificity for monitoring. Strategies involving OCT alone for diagnosis and/or monitoring were unlikely to be cost-effective. Further research is required on (i) the performance of SD-OCT compared with FFA, especially for monitoring but also for diagnosis; (ii) the performance of strategies involving combinations/sequences of tests, for diagnosis and monitoring; (iii) the likelihood of active and inactive nAMD becoming inactive or active respectively; and (iv) assessment of treatment-associated utility weights (e.g. decrements), through a preference-based study.
STUDY REGISTRATION: This study is registered as PROSPERO CRD42012001930.
FUNDING: The National Institute for Health Research Health Technology Assessment programme.
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The use of Raman and anti-stokes Raman spectroscopy to investigate the effect of exposure to high power laser radiation on the crystalline phases of TiO2 has been investigated. Measurement of the changes, over several time integrals, in the Raman and anti-stokes Raman of TiO2 spectra with exposure to laser radiation is reported. Raman and anti-stokes Raman provide detail on both the structure and the kinetic process of changes in crystalline phases in the titania material. The effect of laser exposure resulted in the generation of increasing amounts of the rutile crystalline phase from the anatase crystalline phase during exposure. The Raman spectra displayed bands at 144 cm-1 (A1g), 197 cm-1 (Eg), 398 cm-1 (B1g), 515 cm-1 (A1g), and 640 cm-1 (Eg) assigned to anatase which were replaced by bands at 143 cm-1 (B1g), 235 cm-1 (2 phonon process), 448 cm-1 (Eg) and 612 cm-1 (A1g) which were assigned to rutile. This indicated that laser irradiation of TiO2 changes the crystalline phase from anatase to rutile. Raman and anti-stokes Raman are highly sensitive to the crystalline forms of TiO2 and allow characterisation of the effect of laser irradiation upon TiO2. This technique would also be applicable as an in situ method for monitoring changes during the laser irradiation process
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As part of any drilling cuttings pile removal process the requirement for monitoring the release of contaminants into the marine environment will be critical. Traditional methods for such monitoring involve taking samples for laboratory analysis. This process is time consuming and only provides data on spot samples taken from a limited number of locations and time frames. Such processes, therefore, offer very restricted information. The need for improved marine sensors for monitoring contaminants is established. We report here the development and application of a multi-capability optical sensor for the real-time in situ monitoring of three key marine environmental and offshore/oil parameters: hydrocarbons, synthetic-based fluids and heavy metal concentrations. The use of these sensors will be a useful tool for real-time in situ environmental monitoring during the process of decommissioning offshore structures. Multi-capability array sensors could also provide information on the dispersion of contamination from drill cuttings piles either while they are in situ or during their removal.
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New environmentally acceptable production methods are required to help reduce the environmental impact of many industrial processes. One potential route is the application of photocatalysis using semiconductors. This technique has enabled new environmentally acceptable synthetic routes for organic synthesis which do not require the use of toxic metals as redox reagents. These photocatalysts also have more favourable redox potentials than many traditional reagents. Semiconductor photocatalysis can also be applied to the treatment of polluted effluent or for the destruction of undesirable by-products of reactions. In addition to the clean nature of the process the power requirements of the technique can be relatively low, with some reactions requiring only sunlight.
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A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.
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Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.
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Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.
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Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.
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The UK’s transportation network is supported by critical geotechnical assets (cuttings/embankments/dams) that require sustainable, cost-effective management, while maintaining an appropriate service level to meet social, economic, and environmental needs. Recent effects of extreme weather on these geotechnical assets have highlighted their vulnerability to climate variations. We have assessed the potential of surface wave data to portray the climate-related variations in mechanical properties of a clay-filled railway embankment. Seismic data were acquired bimonthly from July 2013 to November 2014 along the crest of a heritage railway embankment in southwest England. For each acquisition, the collected data were first processed to obtain a set of Rayleigh-wave dispersion and attenuation curves, referenced to the same spatial locations. These data were then analyzed to identify a coherent trend in their spatial and temporal variability. The relevance of the observed temporal variations was also verified with respect to the experimental data uncertainties. Finally, the surface wave dispersion data sets were inverted to reconstruct a time-lapse model of S-wave velocity for the embankment structure, using a least-squares laterally constrained inversion scheme. A key point of the inversion process was constituted by the estimation of a suitable initial model and the selection of adequate levels of spatial regularization. The initial model and the strength of spatial smoothing were then kept constant throughout the processing of all available data sets to ensure homogeneity of the procedure and comparability among the obtained VS sections. A continuous and coherent temporal pattern of surface wave data, and consequently of the reconstructed VS models, was identified. This pattern is related to the seasonal distribution of precipitation and soil water content measured on site.