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Zeitschriftenartikel zum Thema „Measurements uncertainty“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 2. Februar 2022

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1

Białek, Agnieszka, Sarah Douglas, Joel Kuusk, Ilmar Ansko, Viktor Vabson, Riho Vendt und Tânia Casal. „Example of Monte Carlo Method Uncertainty Evaluation for Above-Water Ocean Colour Radiometry“. Remote Sensing 12, Nr. 5 (29.02.2020): 780. http://dx.doi.org/10.3390/rs12050780.

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We describe a method to evaluate an uncertainly budget for the in situ Ocean Colour Radiometric measurements. A Monte Carlo approach is chosen to propagate the measurement uncertainty inputs through the measurements model. The measurement model is designed to address instrument characteristics and uncertainty associated with them. We present the results for a particular example when the radiometers were fully characterised and then use the same data to show a case when such characterisation is missing. This, depending on the measurement and the wavelength, can increase the uncertainty value significantly; for example, the downwelling irradiance at 442.5 nm with fully characterised instruments can reach uncertainty values of 1%, but for the instruments without such characterisation, that value could increase to almost 7%. The uncertainty values presented in this paper are not final, as some of the environmental contributors were not fully evaluated. The main conclusion of this work are the significance of thoughtful instrument characterisation and correction for the most significant uncertainty contributions in order to achieve a lower measurements uncertainty value.

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Shi, Zhao Yao, Jia Chun Lin und Michael Paul Krystek. „Uncertainty Analysis of Helical Deviation Measurements“. Key Engineering Materials 437 (Mai 2010): 212–16. http://dx.doi.org/10.4028/www.scientific.net/kem.437.212.

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The helix is a complex geometrical element. During the process of a dynamical measurement of the helical deviations, many factors, including the machine and the environment, lead to measurement errors. Although ISO as well as national standards stipulate the tolerances and assessment methods for helical deviations, these standards contribute little to the uncertainty calculations concerning such measurements. According to the Guide to the Expression of Uncertainty in Measurement (GUM), all measurement results must have a stated uncertainty associated to them. But in most cases of helical deviation measurements, no uncertainty value is given, simply because no measurement uncertainty calculation procedure exists. For the case of helical deviation measurements on a Computer Numeric Control (CNC) polar coordinate machine, this paper analyses in detail all kinds of factors contributing to the measurement uncertainty, and gives the calculation procedure of the measurement uncertainty of helical deviation. As an example, the calculation of the measurement uncertainty of the helical deviations of a worm is presented.

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Vasilevskyi, О. М., M. Yu Yakovlev und P. I. Kulakov. „SPECTRAL METHOD TO EVALUATE THE UNCERTAINTY OF DYNAMIC MEASUREMENTS“. Tekhnichna Elektrodynamika 2017, Nr. 4 (08.06.2017): 72–78. http://dx.doi.org/10.15407/techned2017.04.072.

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4

Xu, Ning, Jing Fang Guo und Jin Fang Han. „Measurements and Mathematical Characterization of Uncertain Information“. Applied Mechanics and Materials 530-531 (Februar 2014): 591–96. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.591.

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This paper, the problems of mathematical characteristics and measurements for three kind of uncertainty information are descussed by means of the logical analysis method. Firstly, By virtue of the analysis for the importance of uncertain information research in scientific development, a research chain: uncertainty informationinformation theorycomplexity is presented. Secondly, the mathematical characterization and measurements for three kind of uncertainty information are obtained in terms of the characteristic analysis for uncertain information .

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Ritchie, Nicholas W. M. „Embracing Uncertainty: Modeling the Standard Uncertainty in Electron Probe Microanalysis—Part I“. Microscopy and Microanalysis 26, Nr. 3 (21.05.2020): 469–83. http://dx.doi.org/10.1017/s1431927620001555.

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AbstractThis is the first in a series of articles which present a new framework for computing the standard uncertainty in electron excited X-ray microanalysis measurements. This article will discuss the framework and apply it to a handful of simple, but useful, subcomponents of the larger problem. Subsequent articles will handle more complex aspects of the measurement model. The result will be a framework in which sophisticated and practical models of the uncertainty for real-world measurements. It will include many long overlooked contributions like surface roughness and coating thickness. The result provides more than just error bars for our measurements. It also provides a framework for measurement optimization and, ultimately, the development of an expert system to guide both the novice and expert to design more effective measurement protocols.

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Vulevic, Branislav, Cedomir Belic und Luka Perazic. „Measurement uncertainty in broadband radiofrequency radiation level measurements“. Nuclear Technology and Radiation Protection 29, Nr. 1 (2014): 53–57. http://dx.doi.org/10.2298/ntrp1401053v.

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For the evaluation of measurement uncertainty in the measurement of broadband radio frequency radiation, in this paper we propose a new approach based on the experience of the authors of the paper with measurements of radiofrequency electric field levels conducted in residential areas of Belgrade and over 35 municipalities in Serbia. The main objective of the paper is to present practical solutions in the evaluation of broadband measurement uncertainty for the in-situ RF radiation levels.

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Bernstein, Johannes, und Albert Weckenmann. „Measurement uncertainty evaluation of optical multi-sensor-measurements“. Measurement 45, Nr. 10 (Dezember 2012): 2309–20. http://dx.doi.org/10.1016/j.measurement.2011.10.032.

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8

Ray, Jr., Elden F. „Measurement uncertainty in conducting environmental sound level measurements“. Noise Control Engineering Journal 48, Nr. 1 (2000): 8. http://dx.doi.org/10.3397/1.2827978.

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9

Krechmer, Ken. „Relational measurements and uncertainty“. Measurement 93 (November 2016): 36–40. http://dx.doi.org/10.1016/j.measurement.2016.06.058.

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10

McMonnies, Charles W. „Uncertainty of clinical measurements“. Clinical and Experimental Optometry 89, Nr. 5 (September 2006): 332–33. http://dx.doi.org/10.1111/j.1444-0938.2006.00064.x.

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11

Ritchie, Nicholas W. M. „Embracing Uncertainty: Modeling Uncertainty in EPMA—Part II“. Microscopy and Microanalysis 27, Nr. 1 (Februar 2021): 74–89. http://dx.doi.org/10.1017/s1431927620024691.

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AbstractThis, the second in a series of articles present a new framework for considering the computation of uncertainty in electron excited X-ray microanalysis measurements, will discuss matrix correction. The framework presented in the first article will be applied to the matrix correction model called “Pouchou and Pichoir's Simplified Model” or simply “XPP.” This uncertainty calculation will consider the influence of beam energy, take-off angle, mass absorption coefficient, surface roughness, and other parameters. Since uncertainty calculations and measurement optimization are so intimately related, it also provides a starting point for optimizing accuracy through choice of measurement design.

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Rasul, SB, A. Monsur Kajal und AH Khan. „Quantifying Uncertainty in Analytical Measurements“. Journal of Bangladesh Academy of Sciences 41, Nr. 2 (29.01.2018): 145–63. http://dx.doi.org/10.3329/jbas.v41i2.35494.

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In providing chemical, biochemical and agricultural materials testing services for quality specification, the analytical chemists are increasingly required to address the fundamental issues related to the modern concepts of Chemical Metrology such as Method Validation, Traceability and Uncertainty of Measurements. Without this knowledge, the results cannot be recognized as a scientific fact with defined level of acceptability. According to ISO/IEC 17025:2005, this is an essential requirement of all testing laboratories to attain competence to test materials for the desired purpose. of these three concepts of chemical metrology, the most complex is the calculation of uncertainties from different sources associated with a single measurement and incorporate them into the final result(s) as the expanded uncertainty(UE) with a defined level of reliability (e.g., at 95% CL). In this paper the concepts and practice of uncertainty calculation in analytical measurements are introduced by using the principles of statistics. The calculation procedure indentifies the primary sources of uncertainties and quantifies their respective contributions to the total uncertainty of the final results. The calculations are performed by using experimental data of Lead (Pb) analysis in soil by GF-AAS and pesticides analysis in wastewater by GC-MS method. The final result of the analytical measurement is expressed as: Result (mg/kg) = Measured Value of Analyte (mg/kg) ± Uncertainty (mg/kg), where the uncertainty is the parametric value associated with individual steps in measurements such as sample weighing(Um), extraction of analyte (Ue) (Pb from soil or pesticides from water), volumetry in measurement (Uv), concentration calibration(Ux), etc. The propagation of these individual uncertainties from different sources is expressed as combined relative uncertainty (Uc), which is calculated by using the formula:Combined uncertainty Uc/c = {(Ux/x)2+(Um/m)2+(Uv/v)2+(Ue/e)2+…}1/2The overall uncertainty associated with the final result of the analyte is expressed as Expanded Uncertainty (UE) at certain level of confidence (e.g. 95%). The Expanded Uncertainty is calculated by multiplication of Combined Uncertainty (Uc) with a coverage factor (K) according to the proposition of level of confidence. In general, the level of confidence for enormous data is considered at 95%, CL where K is 2. Hence, the final result of the analyte is expressed as: X ± UE (unit) at 95% CL, where UE = 2Uc.Journal of Bangladesh Academy of Sciences, Vol. 41, No. 2, 145-163, 2017

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Kristiansen, Jesper. „The Guide to Expression of Uncertainty in Measurement Approach for Estimating Uncertainty“. Clinical Chemistry 49, Nr. 11 (01.11.2003): 1822–29. http://dx.doi.org/10.1373/clinchem.2003.021469.

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Abstract Background: The aim of the Guide to Expression of Uncertainty in Measurement (GUM) is to harmonize the different practices for estimating and reporting uncertainty of measurement. Although there are clear advantages in having a common approach for evaluating uncertainty, application of the GUM approach to chemistry measurements is not straightforward. In the above commentary, Krouwer suggests that the GUM approach should not be applied to diagnostic assays, because (a) the quality of diagnostic assays is to low, and (b) the GUM uncertainty intervals are too narrow to predict the outliers that occasionally trouble these methods. Methods: Some of the examples presented by Krouwer are reviewed. Sodium measurements are modeled mathematically to illustrate the GUM approach to uncertainty. A standardized uncertainty evaluation process is presented. Results: Modeling of sodium measurements demonstrates how the GUM uncertainty interval reflects the treatment of a bias: The width of the uncertainty interval varied depending on whether a correction for a calibrator lot bias was applied, but in both cases it was consistent with the distribution of measurement results. Expanding the uncertainty interval to include outliers runs counter to the definition of uncertainty. Used appropriately, the GUM uncertainty can be helpful in detecting outliers. In standardizing the uncertainty evaluation, the importance of the analytical imprecision and traceability was emphasized. It is problematic that manufacturers of commercial assays rarely inform about the uncertainty of the values assigned to the calibrators. As demonstrated by an example, external quality-assurance data may be used to estimate this uncertainty. Conclusions: The GUM uncertainty should be applied to measurements in laboratory medicine because it may actually support the forces that drive the work on improving the quality of measurement procedures. However, it is important that the GUM approach is made more manageable by standardizing the uncertainty evaluation procedure as much as possible. It is essential to focus on the traceability and uncertainty of calibrators and reagents supplied by manufacturers of assays. Information about uncertainty is necessary in the evaluation of the uncertainty associated with manufacturers’ measurement procedures, and in general it may force manufacturers to increase their efforts in improving the metrologic and analytical quality of their products.

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Shrestha, Rajesh R., und Slobodan P. Simonovic. „Fuzzy set theory based methodology for the analysis of measurement uncertainties in river discharge and stage“. Canadian Journal of Civil Engineering 37, Nr. 3 (März 2010): 429–40. http://dx.doi.org/10.1139/l09-151.

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The discharge and stage measurements in a river system are characterized by a number of sources of uncertainty, which affects the accuracy of a rating curve established from measurements. This paper presents a fuzzy set theory based methodology for consideration of different sources of uncertainty in the stage and discharge measurements and their aggregation into a combined uncertainty. The uncertainty in individual measurements of stage and discharge is represented using triangular fuzzy numbers, and their spread is determined according to the International Organization for Standardization (ISO) standard 748 guidelines. The extension principle based fuzzy arithmetic is used for the aggregation of various uncertainties into overall stage–discharge measurement uncertainty. In addition, a fuzzified form of ISO 748 formulation is used for the calculation of combined uncertainty and comparison with the fuzzy aggregation method. The methodology developed in this paper is illustrated with a case study of the Thompson River near Spences Bridge in British Columbia, Canada. The results of the case study show that the selection of number of velocity measurement points on a vertical is the largest source of uncertainty in discharge measurement. An increase in the number of velocity measurement points provides the most effective reduction in the overall uncertainty. The next most important source of uncertainty for the case study location is the number of verticals used for velocity measurements. The study also shows that fuzzy set theory provides a suitable methodology for the uncertainty analysis of stage–discharge measurements.

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Logar, John. „Accounting for Measurement Uncertainty and Variability in Dose Measurements“. Biomedical Instrumentation & Technology 50, s3 (01.04.2016): 3–8. http://dx.doi.org/10.2345/0899-8205-50.s3.3.

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16

Fischer, Andreas. „Limiting Uncertainty Relations in Laser-Based Measurements of Position and Velocity Due to Quantum Shot Noise“. Entropy 21, Nr. 3 (08.03.2019): 264. http://dx.doi.org/10.3390/e21030264.

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With the ongoing progress of optoelectronic components, laser-based measurement systems allow measurements of position as well as displacement, strain and velocity with unbeatable speed and low measurement uncertainty. The performance limit is often studied for a single measurement setup, but a fundamental comparison of different measurement principles with respect to the ultimate limit due to quantum shot noise is rare. For this purpose, the Cramér-Rao bound is described as a universal information theoretic tool to calculate the minimal achievable measurement uncertainty for different measurement techniques, and a review of the respective lower bounds for laser-based measurements of position, displacement, strain and velocity at particles and surfaces is presented. As a result, the calculated Cramér-Rao bounds of different measurement principles have similar forms for each measurand including an indirect proportionality with respect to the number of photons and, in case of the position measurement for instance, the wave number squared. Furthermore, an uncertainty principle between the position uncertainty and the wave vector uncertainty was identified, i.e., the measurement uncertainty is minimized by maximizing the wave vector uncertainty. Additionally, physically complementary measurement approaches such as interferometry and time-of-flight positions measurements as well as time-of-flight and Doppler particle velocity measurements are shown to attain the same fundamental limit. Since most of the laser-based measurements perform similar with respect to the quantum shot noise, the realized measurement systems behave differently only due to the available optoelectronic components for the concrete measurement task.

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He, Qin Shu, Shi Fu Xiao und Xin En Liu. „Application of ANN and SVM for Uncertainty Quantification and Propagation“. Advanced Materials Research 230-232 (Mai 2011): 192–96. http://dx.doi.org/10.4028/www.scientific.net/amr.230-232.192.

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All measurements have error that obscures the true value. The error creates uncertainty about the quality of the measured value, which is requiring testing and calibration laboratories to provide estimates of uncertainty with their measurements. Measurement uncertainties include input uncertainty, the propagation of input uncertainty, the output uncertainty and the systematic error uncertainty. Several methods for estimating the uncertainty of measurements have been introduced for different kinds of uncertainty quantification, and two data mining methodologies-Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used to build the unknown propagation model. This paper will discuss the quantification of measurement uncertainty (MU) and the separation of various uncertainty sources to MU and will discuss the advantages and limitations of SVM and ANN for building the propagation model of MU.

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Scott, E. Marian, Gordon T. Cook und Philip Naysmith. „Error and Uncertainty in Radiocarbon Measurements“. Radiocarbon 49, Nr. 2 (2007): 427–40. http://dx.doi.org/10.1017/s0033822200042351.

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All measurement is subject to error, which creates uncertainty. Every time that an analytical radiocarbon measurement is repeated under identical conditions on an identical sample (even if this were possible), a different result is obtained. However, laboratories typically make only 1 measurement on a sample, but they are still able to provide an estimate of the analytical uncertainty that reflects the range of values (or the spread) in results that would have been obtained were the measurement to be repeated many times under identical conditions. For a single measured 14C age, the commonly quoted error is based on counting statistics and is used to determine the uncertainty associated with the 14C age. The quoted error will include components due to other laboratory corrections and is assumed to represent the spread we would see were we able to repeat the measurement many times.Accuracy and precision in 14C dating are much desired properties. Accuracy of the measurement refers to the deviation (difference) of the measured value from the true value (or sometimes expected or consensus value), while precision refers to the variation (expected or observed) in a series of replicate measurements. Quality assurance and experimental assessment of these properties occupy much laboratory time through measurement of standards (primary and secondary), reference materials, and participation in interlaboratory trials. This paper introduces some of the most important terms commonly used in 14C dating and explains, through some simple examples, their interpretation.

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Pillarz, Marc, Axel von Freyberg, Dirk Stöbener und Andreas Fischer. „Gear Shape Measurement Potential of Laser Triangulation and Confocal-Chromatic Distance Sensors“. Sensors 21, Nr. 3 (30.01.2021): 937. http://dx.doi.org/10.3390/s21030937.

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The demand for extensive gear shape measurements with single-digit µm uncertainty is growing. Tactile standard gear tests are precise but limited in speed. Recently, faster optical gear shape measurement systems have been examined. Optical gear shape measurements are challenging due to potential deviation sources such as the tilt angles between the surface normal and the sensor axis, the varying surface curvature, and the surface properties. Currently, the full potential of optical gear shape measurement systems is not known. Therefore, laser triangulation and confocal-chromatic gear shape measurements using a lateral scanning position measurement approach are studied. As a result of tooth flank standard measurements, random effects due to surface properties are identified to primarily dominate the achievable gear shape measurement uncertainty. The standard measurement uncertainty with the studied triangulation sensor amounts to >10 µm, which does not meet the requirements. The standard measurement uncertainty with the confocal-chromatic sensor is <6.5 µm. Furthermore, measurements on a spur gear show that multiple reflections do not influence the measurement uncertainty when measuring with the lateral scanning position measurement approach. Although commercial optical sensors are not designed for optical gear shape measurements, standard uncertainties of <10 µm are achievable for example with the applied confocal-chromatic sensor, which indicates the further potential for optical gear shape measurements.

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Bartel, T. „Uncertainty in NIST force measurements“. Journal of Research of the National Institute of Standards and Technology 110, Nr. 6 (November 2005): 589. http://dx.doi.org/10.6028/jres.110.084.

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Bich, Walter, und Francesca Pennecchi. „Uncertainty in measurements by counting“. Metrologia 49, Nr. 1 (07.11.2011): 15–19. http://dx.doi.org/10.1088/0026-1394/49/1/003.

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Yang, Jia, Elbara Ziade und Aaron J. Schmidt. „Uncertainty analysis of thermoreflectance measurements“. Review of Scientific Instruments 87, Nr. 1 (Januar 2016): 014901. http://dx.doi.org/10.1063/1.4939671.

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23

González, A. Gustavo, und M. Ángeles Herrador. „Accuracy profiles from uncertainty measurements“. Talanta 70, Nr. 4 (November 2006): 896–901. http://dx.doi.org/10.1016/j.talanta.2006.02.010.

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24

Ostermeyer, G. P., M. Mueller, T. Srisupattarawanit und A. Voelpel. „On Uncertainty in Friction Measurements“. PAMM 17, Nr. 1 (Dezember 2017): 63–66. http://dx.doi.org/10.1002/pamm.201710019.

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Makarewicz, Rufin, und Roman Gołębiewski. „Uncertainty minimization in LAeqT measurements“. Noise Control Engineering Journal 60, Nr. 1 (01.01.2012): 121–23. http://dx.doi.org/10.3397/1.3676742.

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Chiorboli, G. „Sub-picosecond aperture-uncertainty measurements“. IEEE Transactions on Instrumentation and Measurement 51, Nr. 5 (Oktober 2002): 1039–44. http://dx.doi.org/10.1109/tim.2002.807799.

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Golubev, É. A. „Uncertainty of Measurements. Part 1“. Measurement Techniques 46, Nr. 10 (Oktober 2003): 924–30. http://dx.doi.org/10.1023/b:mete.0000010778.00355.bc.

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Golubev, É. A. „Uncertainty of Measurements. Part 2“. Measurement Techniques 46, Nr. 11 (November 2003): 1022–28. http://dx.doi.org/10.1023/b:mete.0000014432.78953.4c.

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29

Baez, John C., und S. Jay Olson. „Uncertainty in measurements of distance“. Classical and Quantum Gravity 19, Nr. 14 (21.06.2002): L121—L125. http://dx.doi.org/10.1088/0264-9381/19/14/101.

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SICOE, Gina Mihaela. „Uncertainty of measurement -Important parameter for product conformity assessment“. University of Pitesti. Scientific Bulletin - Automotive Series 30, Nr. 1 (01.11.2020): 1–6. http://dx.doi.org/10.26825/bup.ar.2020.008.

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The measurements are widely used to ensure the quality of products. It is known that the measurement process is influenced by many factors which lead to measurement errors. The uncertainty of measurement is an essential parameter because the expression of the results accompanied by uncertainty offers more confidence in the results. The research presented in this article focuses on methods forcalculating uncertainty and explaining the rules for making decisions when we use uncertainty. Two case studies are presented, one for dimensional measurements and the other for the estimation of the uncertainty of Vickers hardness measurement for one material, steel OLC15, in order to establish the relevance of the results and quality assessment. The results obtained on several measurements and the uncertainties of measurement associated are presented in the article and a discussion of the results is undertaken.

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Moffat, R. J. „The measurement chain and validation of experimental measurements“. ACTA IMEKO 3, Nr. 1 (07.05.2014): 16. http://dx.doi.org/10.21014/acta_imeko.v3i1.196.

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<p>This is a reissue of a paper which appeared in ACTA IMEKO 1973, Proceedings of the 6th Congress of the International Measurement Confederation, "Measurement and instrumentation", 17.-23.6.1973, Dresden, vol. 1, pp. 45-53.</p><p>The paper witnesses the sophisticated discussion that, well before the publication of the Guide to the Expression of Uncertainty in Measurement (GUM), was active in the measurement science community around the subject of error and uncertainty, and its consequences on the structure of the measuring process and the way it is performed.</p>

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Siebert, T., E. Hack, G. Lampeas, E. A. Patterson und K. Splitthof. „Uncertainty Quantification for DIC Displacement Measurements in Industrial Environments“. Experimental Techniques 45, Nr. 5 (16.02.2021): 685–94. http://dx.doi.org/10.1007/s40799-021-00447-3.

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AbstractBackground: most methods of uncertainty quantification for digital image correlation are orientated towards the research environment and it remains difficult to quantify all of the uncertainty introduced along the measurement chain in an industrial environment. This gap in capability can become critical when physical tests are required for certification purposes. Objective: To develop and demonstrate an uncertainty quantification method that was independent of a specific DIC system, easily integrated with the measurement workflow, applicable at the measurement location and capable of capturing the contributions from all sources of uncertainty. Methods: an elegant new method utilises the calibration target, commonly used with DIC systems to evaluate their intrinsic and extrinsic parameters, through reference measurements before and after relative motion between the measurement system and the object of interest. The method is described and demonstrated for quantifying the field of uncertainty associated with maps of displacement and deformation in a large-scale industrial component. Results: The fields of uncertainty associated with measurements, using stereoscopic DIC, of x-, y- and z- displacement components during a compression buckling test on an aircraft fuselage panel are presented. The derived uncertainty has independently been corroborated along one axis by moving a calibrated translation stage. Conclusions: A new method has been proposed that allows the quantification of the fields of uncertainty arising from all sources when DIC measurements are performed on a large-scale object of interest in an industrial environment. The method requires no additional equipment and can be readily included in the workflow of a measurement campaign.

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Zhang, Ya, Jian Zhong Fu und Zi Chen Chen. „Application of Monte Carlo Method in the Measurement Process Design According to next Generation of GPS“. Advanced Materials Research 189-193 (Februar 2011): 96–101. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.96.

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Measurement process has an important impact on the reliability of measurement. The reliability of measurement is weighed by measurement uncertainty. It is very difficult to estimate the uncertainty in the indirect measurements according to the transfer formula given by GUM (Guide to the Expression of Uncertainty in Measurement). Monte Carlo method was proposed to solve the problem of uncertainty estimation and seek suitable measurement process in the indirect measurements. The mathematical relation between the measurand and the direct measures is established firstly. Then Monte Carlo method was adopted to conduct the sampling and synthesis of measurement uncertainty contributors. At last, the measurement method was evaluated and improved according to Procedure for Uncertainty Management, which is given by next generation of GPS (Geometrical Product Specification). Experimental result shows that Monte Carlo Simulation method has a good application foreground in the uncertainty estimation and measurement process design.

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Clasing, Robert, und Enrique Muñoz. „Estimating the Optimal Velocity Measurement Time in Rivers’ Flow Measurements: An Uncertainty Approach“. Water 10, Nr. 8 (31.07.2018): 1010. http://dx.doi.org/10.3390/w10081010.

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The gauging process can be very extensive and time-consuming due to the procedures involved. Since velocity measurement time (VMT) is one of the main variables that would allow gauging times to be reduced, this study seeks to determine the optimal point VMT and, thereby, reduce the overall gauging time. An uncertainty approach based on the USGS area-velocity method and the GLUE methodology applied to eight gauging samples taken in shallow rivers located in South-central Chile was used. The average point velocity was calculated as the average of 1 to 70 randomly selected instant velocity samples (taken every one second). The time at which the uncertainty bands reached a stability criterion (according to both width and slope stability) was considered to be the optimum VMT since the variations were negligible and it does not further contribute to a less uncertain solution. Based on the results, it is concluded that the optimum point VMT is 17 s. Therefore, a point velocity measurement of 20 s is recommended as the optimal time for gauging in shallow rivers.

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Maciejewski, Paul K. „Elements of an Approach to the Assessment of Systematic Uncertainty in Transient Measurements“. Journal of Fluids Engineering 120, Nr. 4 (01.12.1998): 755–59. http://dx.doi.org/10.1115/1.2820734.

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Although there has been an increasing interest in experimental research investigating time-dependent fluid phenomena, accepted methods for assessing and reporting measurement uncertainty, i.e., those contained in ANSI/ASME PTC 1991-1998. do not consider issues pertaining specifically to the assessment of uncertainty in transient measurements. Complementing the author’s previous work which presented a method for assessing the random component of uncertainty in transient measurements, this paper presents a method for assessing the systematic component of uncertainty in transient measurements.

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Venteris, E. R., und I. M. Whillans. „Variability of accumulation rate in the catchments of Ice Streams B, C, D and E, Antarctica“. Annals of Glaciology 27 (1998): 227–30. http://dx.doi.org/10.3189/1998aog27-1-227-230.

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A model of error and variability in snow arrumulation rate is formulated to determine the reliability of accumulation-rate point measurements as regional and temporal means. The uncertainty model is applied to data from 70 shallow firn cores covering the Ross Sea drainage of the West Antarctic ice sheet. The model includes measurement error, local spatial variation and time variation. Average uncertainly in accumulation rate is 0.016maice equivalent or about 15%. Considering that measurement and depositional uncertainties are independent from core-to-core, an uncertainty of 0.01 m a−1 applies when many values are used to integrate accumulation rate over a catchment.

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Ruffa, S., G. D. Panciani, F. Ricci und G. Vicario. „Assessing measurement uncertainty in CMM measurements: comparison of different approaches“. International Journal of Metrology and Quality Engineering 4, Nr. 3 (2013): 163–68. http://dx.doi.org/10.1051/ijmqe/2013057.

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38

Giyanani, A., W. Bierbooms und G. van Bussel. „Lidar uncertainty and beam averaging correction“. Advances in Science and Research 12, Nr. 1 (13.05.2015): 85–89. http://dx.doi.org/10.5194/asr-12-85-2015.

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Abstract. Remote sensing of the atmospheric variables with the use of Lidar is a relatively new technology field for wind resource assessment in wind energy. A review of the draft version of an international guideline (CD IEC 61400-12-1 Ed.2) used for wind energy purposes is performed and some extra atmospheric variables are taken into account for proper representation of the site. A measurement campaign with two Leosphere vertical scanning WindCube Lidars and metmast measurements is used for comparison of the uncertainty in wind speed measurements using the CD IEC 61400-12-1 Ed.2. The comparison revealed higher but realistic uncertainties. A simple model for Lidar beam averaging correction is demonstrated for understanding deviation in the measurements. It can be further applied for beam averaging uncertainty calculations in flat and complex terrain.

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Joannis, C., G. Ruban, M. C. Gromaire, J. L. Bertrand-Krajewski und G. Chebbo. „Reproducibility and uncertainty of wastewater turbidity measurements“. Water Science and Technology 57, Nr. 10 (01.05.2008): 1667–73. http://dx.doi.org/10.2166/wst.2008.292.

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Turbidity monitoring is a valuable tool for operating sewer systems, but it is often considered as a somewhat tricky parameter for assessing water quality, because measured values depend on the model of sensor, and even on the operator. This paper details the main components of the uncertainty in turbidity measurements with a special focus on reproducibility, and provides guidelines for improving the reproducibility of measurements in wastewater relying on proper calibration procedures. Calibration appears to be the main source of uncertainties, and proper procedures must account for uncertainties in standard solutions as well as non linearity of the calibration curve. With such procedures, uncertainty and reproducibility of field measurement can be kept lower than 5% or 25 FAU. On the other hand, reproducibility has no meaning if different measuring principles (attenuation vs. nephelometry) or very different wavelengths are used.

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Demirel, Bülent, Stephan Sponar und Yuji Hasegawa. „Measurements of Entropic Uncertainty Relations in Neutron Optics“. Applied Sciences 10, Nr. 3 (06.02.2020): 1087. http://dx.doi.org/10.3390/app10031087.

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The emergence of the uncertainty principle has celebrated its 90th anniversary recently. For this occasion, the latest experimental results of uncertainty relations quantified in terms of Shannon entropies are presented, concentrating only on outcomes in neutron optics. The focus is on the type of measurement uncertainties that describe the inability to obtain the respective individual results from joint measurement statistics. For this purpose, the neutron spin of two non-commuting directions is analyzed. Two sub-categories of measurement uncertainty relations are considered: noise–noise and noise–disturbance uncertainty relations. In the first case, it will be shown that the lowest boundary can be obtained and the uncertainty relations be saturated by implementing a simple positive operator-valued measure (POVM). For the second category, an analysis for projective measurements is made and error correction procedures are presented.

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Danai, Kourosh, und Hsinyung Chin. „Fault Diagnosis With Process Uncertainty“. Journal of Dynamic Systems, Measurement, and Control 113, Nr. 3 (01.09.1991): 339–43. http://dx.doi.org/10.1115/1.2896416.

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A nonparametric pattern classification method is introduced for fault diagnosis of complex systems. This method represents the fault signatures by the columns of a multi-valued influence matrix (MVIM), and uses adaptation to cope with fault signature variability. In this method, the measurements are monitored on-line and flagged upon the detection of an abnormality. Fault diagnosis is performed by matching this vector of flagged measurements against the columns of the influence matrix. The MVIM method has the capability to assess the diagnosability of the system, and use that as the basis for sensor selection and optimization. It also uses diagnostic error feedback for adaptation, which enables it to estimate its diagnostic model based upon a small number of measurement-fault data.

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Ding, Lijun, Shuguang Dai und Pingan Mu. „Point cloud measurements-uncertainty calculation on spatial-feature based registration“. Sensor Review 39, Nr. 1 (21.01.2019): 129–36. http://dx.doi.org/10.1108/sr-02-2018-0043.

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Purpose Measurement uncertainty calculation is an important and complicated problem in digitised components inspection. In such inspections, a coordinate measuring machine (CMM) and laser scanner are usually used to get the surface point clouds of the component in different postures. Then, the point clouds are registered to construct fully connected point clouds of the component’s surfaces. However, in most cases, the measurement uncertainty is difficult to estimate after the scanned point cloud has been registered. This paper aims to propose a simplified method for calculating the uncertainty of point cloud measurements based on spatial feature registration. Design/methodology/approach In the proposed method, algorithmic models are used to calculate the point cloud measurement uncertainty based on noncontact measurements of the planes, lines and points of the component and spatial feature registration. Findings The measurement uncertainty based on spatial feature registration is related to the mutual position of registration features and the number of sensor commutation in the scanning process, but not to the spatial distribution of the measured feature. The results of experiments conducted verify the efficacy of the proposed method. Originality/value The proposed method provides an efficient algorithm for calculating the measurement uncertainty of registration point clouds based on part features, and therefore has important theoretical and practical significance in digitised components inspection.

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Shen, Y., und N. A. Duffie. „An Uncertainty Analysis Method for Coordinate Referencing in Manufacturing Systems“. Journal of Engineering for Industry 117, Nr. 1 (01.02.1995): 42–48. http://dx.doi.org/10.1115/1.2803276.

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Accurate and consistent transformations between design and manufacturing coordinate systems are essential for high quality part production. Fixturing and coordinate measurement are common coordinate referencing techniques which are used to locate points or measurement points on workpiece reference surfaces to establish these coordinate transformations. However, uncertainty sources such as geometric form deviations in workpiece surfaces, tolerances on fixture locators, and errors in coordinate measurements exist. A result is that coordinate transformations established using the locating and measurement points are in herently uncertain. An uncertainty analysis method for coordinate referencing is presented in this paper. The uncertainty interval concept is used to describe essential characteristics of uncertainty sources in coordinate referencing and coordinate transformation relationships. The method is applied to estimating uncertainties in simple and compound coordinate transformation obtained using coordinate referencing in an experimental mold manufacturing system. Results of Monte Carlo simulations are used to show that the uncertainty analysis method gives a consistent and high percentage of coverage in evaluating coordinate referencing in the examples studied.

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Pareja, T. F., und J. L. G. Pallero. „Uncertainty Assessment in Terrestrial Laser Scanner Measurements“. Key Engineering Materials 615 (Juni 2014): 88–94. http://dx.doi.org/10.4028/www.scientific.net/kem.615.88.

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Abstract. The essential purpose of this study is to develop the measurement procedures in order toevaluate the quality of the observations carried out using Terrestrial Laser Scanner (TLS) equipment.It tries, in addition, to estimate an uncertainty value that allows the users to know the reliability of theinstrument measurements. The fundamental idea of this paper is to show the metrological control'sneed, and the quality of measure's evaluation for TLS equipment and to describe a working methodology,able to be reproducible, without the essential need of having a very complex infrastructure.

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Cecinati, Francesca, Antonio Moreno-Ródenas, Miguel Rico-Ramirez, Marie-claire ten Veldhuis und Jeroen Langeveld. „Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data“. Atmosphere 9, Nr. 11 (14.11.2018): 446. http://dx.doi.org/10.3390/atmos9110446.

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In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often necessary. The uncertainty associated with rain gauge measurements is dependent on rainfall intensity and on the characteristics of the devices. Common spatial interpolation methods do not account for rain gauge uncertainty variability. Kriging for Uncertain Data (KUD) allows the handling of the uncertainty of each rain gauge independently, modelling space- and time-variant errors. The applications of KUD to rain gauge interpolation and radar-gauge rainfall merging are studied and compared. First, the methodology is studied with synthetic experiments, to evaluate its performance varying rain gauge density, accuracy and rainfall field characteristics. Subsequently, the method is applied to a case study in the Dommel catchment, the Netherlands, where high-quality automatic gauges are complemented by lower-quality tipping-bucket gauges and radar composites. The case study and the synthetic experiments show that considering measurement uncertainty in rain gauge interpolation usually improves rainfall estimations, given a sufficient rain gauge density. Considering measurement uncertainty in radar-gauge merging consistently improved the estimates in the tested cases, thanks to the additional spatial information of radar rainfall data but should still be used cautiously for convective events and low-density rain gauge networks.

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Kozhevnikov, V. V. „CALCULATION OF MEASUREMENTS UNCERTAINTY AT CARRYING OUT OF BALLISTIC RESEARCHES“. Theory and Practice of Forensic Science and Criminalistics 17 (29.11.2017): 236–45. http://dx.doi.org/10.32353/khrife.2017.30.

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Today one of the priority problems is receiving an accreditation certificate under the international standard ISO/IEC 17025:2006 by measurement laboratories of Expert service subdivision of the Ministry of Internal Affairs of Ukraine. One of the requirements which is shown to the accredited testing laboratories, is a presence of uncertainty estimation procedure and ability to apply it. As the ballistic researches are one of the important directions of researches which are carried out in the expert subdivisions, therefore the paper is devoted to the consideration ofa question of uncertainty calculation in such measurements. In the mathematical statistics two types of paramètres which characterize dispersion of not correlated random variables are known: a root-mean-square deviation and a confidential interval. As the characteristics of uncertainty they are applied under the title standard and expanded uncertainty. An elementary estimation of measurements result and its uncertainty is carried out in such an order: description of the measured quantity; revealing of uncertainty sources; quantitative description uncertainty constituents (there are estimated uncertainty constituents which can be received a posteriori or a priori); calculation of standard uncertainty of each source, total standard uncertainty and expanded uncertainty. A posterior estimation is possible only in the case of carrying out multiple observations of the measured quantity (standard uncertainty of type A). An a priori estimation is carried out when multiple observations are not performed. In this case it’s necessary to use the information received from the measurements performed before, from the passport data on the facilities ofmeasuring technics orfrom reference books (standard uncertainty of type B). Short consideration of uncertainty concept, elucidation of the basic stages measurements result estimation and its uncertainty gives the chance to transform the theoretical knowledge into practical application of uncertainty estimation on examples of measurements uncertainty calculation during carrying out ballistic ammunition researches by two different ways.

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Alfieri, Joseph G., William P. Kustas, John H. Prueger, Lawrence E. Hipps, José L. Chávez, Andrew N. French und Steven R. Evett. „Intercomparison of Nine Micrometeorological Stations during the BEAREX08 Field Campaign“. Journal of Atmospheric and Oceanic Technology 28, Nr. 11 (01.11.2011): 1390–406. http://dx.doi.org/10.1175/2011jtech1514.1.

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Abstract Land–atmosphere interactions play a critical role in regulating numerous meteorological, hydrological, and environmental processes. Investigating these processes often requires multiple measurement sites representing a range of surface conditions. Before these measurements can be compared, however, it is imperative that the differences among the instrumentation systems are fully characterized. Using data collected as a part of the 2008 Bushland Evapotranspiration and Agricultural Remote Sensing Experiment (BEAREX08), measurements from nine collocated eddy covariance (EC) systems were compared with the twofold objective of 1) characterizing the interinstrument variation in the measurements, and 2) quantifying the measurement uncertainty associated with each system. Focusing on the three turbulent fluxes (heat, water vapor, and carbon dioxide), this study evaluated the measurement uncertainty using multiple techniques. The results of the analyses indicated that there could be substantial variability in the uncertainty estimates because of the advective conditions that characterized the study site during the afternoon and evening hours. However, when the analysis was limited to nonadvective, quasi-normal conditions, the response of the nine EC stations were remarkably similar. For the daytime period, both the method of Hollinger and Richardson and the method of Mann and Lenschow indicated that the uncertainty in the measurements of sensible heat, latent heat, and carbon dioxide flux were approximately 13 W m−2, 27 W m−2, and 0.10 mg m−2 s−1, respectively. Based on the results of this study, it is clear that advection can greatly increase the uncertainty associated with EC flux measurements. Since these conditions, as well as other phenomena that could impact the measurement uncertainty, are often intermittent, it may be beneficial to conduct uncertainty analyses on an ongoing basis.

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Bredemann, Judith, und Robert H. Schmitt. „Task-specific uncertainty estimation for medical CT measurements“. Journal of Sensors and Sensor Systems 7, Nr. 2 (20.12.2018): 627–35. http://dx.doi.org/10.5194/jsss-7-627-2018.

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Abstract. Computed tomography (CT) is an important imaging technology for medical diagnosis purposes. However, by improving the CT scanners with regard to scan resolution and times, the use of CT is no longer limited to the diagnostic field. Different minimally invasive procedures are image-guided. CT-based surgical navigation utilizes 3-D measurements. Therefore, uncertainties in the imaging and image processing lead to erroneous initial conditions for the navigation process and result in a higher risk of unintended injuries of anatomical risk structures. To minimize the risk of unintended injuries, the uncertainties of the imaging process need to be estimated and considered during the planning of minimally invasive surgery. The estimation of uncertainties for medical measurements is still at the beginning though. Within this contribution, we show that it is important to consider the uncertainty of different measurement tasks during surgical planning using the example of minimally invasive surgery to the lateral skull base. A method for the task-specific uncertainty estimation is used to estimate the uncertainties for defined measurement tasks. Afterwards, we will discuss how the results have to be considered during the surgical planning process.

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Chen, Bin, und Shao-Ming Fei. „Complementary measurement-induced quantum uncertainty based on metric adjusted skew information“. International Journal of Quantum Information 18, Nr. 08 (Dezember 2020): 2150001. http://dx.doi.org/10.1142/s0219749921500015.

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We investigate complementary measurement-induced quantum uncertainty based on metric adjusted skew information, and propose two new measures of quantum uncertainty associated with mutually unbiased measurements and general symmetric informationally complete measurements, respectively. Based on these measures of quantum uncertainty, we present two entanglement criteria and show that they detect better entanglement than the existing corresponding criteria by detailed examples.

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Phillips, S. D., B. Toman und W. T. Estler. „Uncertainty due to finite resolution measurements“. Journal of Research of the National Institute of Standards and Technology 113, Nr. 3 (Mai 2008): 143. http://dx.doi.org/10.6028/jres.113.011.

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