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Journal articles on the topic 'Measurement uncertainty'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Chunovkina, A. G. "Measurement error, measurement uncertainty, and measurand uncertainty." Measurement Techniques 43, no. 7 (2000): 581–86. http://dx.doi.org/10.1007/bf02503592.

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2

Białek, Agnieszka, Sarah Douglas, Joel Kuusk, et al. "Example of Monte Carlo Method Uncertainty Evaluation for Above-Water Ocean Colour Radiometry." Remote Sensing 12, no. 5 (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 si

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3

Johnson, Steven, and Anja Einseln. "An Uncertain Approach to Measurement Uncertainty." Forensic Science International: Synergy 1 (August 2019): S2. http://dx.doi.org/10.1016/j.fsisyn.2019.06.008.

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4

Ferrero, A., and S. Salicone. "Measurement uncertainty." IEEE Instrumentation and Measurement Magazine 9, no. 3 (2006): 44–51. http://dx.doi.org/10.1109/mim.2006.1637979.

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5

Meyer, Veronika R. "Measurement uncertainty." Journal of Chromatography A 1158, no. 1-2 (2007): 15–24. http://dx.doi.org/10.1016/j.chroma.2007.02.082.

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6

Wan, Xiao Xia, Xin Guo Huang, and Zhen Liu. "Uncertainty Evaluation of Spectral Color Measurement." Advanced Materials Research 174 (December 2010): 36–39. http://dx.doi.org/10.4028/www.scientific.net/amr.174.36.

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Uncertainty evaluation of spectral color measurement is the best method of evaluation of color measurement result’s quality. Firstly type A and type B uncertainty of spectral reflectance are analyzed based on different uncertainty's sources, secondly uncertainty of chromaticity parameters are calculated based on spectral reflectance’s uncertainty. Lastly practicability of uncertainty evaluation of spectral color measurement is proved by experiments.

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7

Shi, Zhao Yao, Jia Chun Lin, and Michael Paul Krystek. "Uncertainty Analysis of Helical Deviation Measurements." Key Engineering Materials 437 (May 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 devia

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Chornoivanenko, Kateryna, and Yevhen Povzlo. "EVALUATION OF MICROHARDNESS UNCERTAINTY COMPONENTS OF COMPOSITE MATERIAL." Measuring Equipment and Metrology 86, no. 2 (2025): 73–79. https://doi.org/10.23939/istcmtm2025.02.073.

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The study substantiates the necessity of evaluating measurement uncertainty in the context of product quality control. The evaluation of uncertainty in determining measurement accuracy provides an evidence-based approach to verifying whether the measured quality characteristic complies with established standards. The process of uncertainty evaluation in quality control is complex and labor-intensive, involving the identification of uncertainty sources, detection of correlations among input quantities, determination of probability distribution laws of influencing factors, calculation of sensiti

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9

Zhang, Ya, Jian Zhong Fu, and Zi Chen Chen. "Application of Monte Carlo Method in the Measurement Process Design According to next Generation of GPS." Advanced Materials Research 189-193 (February 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 wa

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10

Fischer, Andreas. "Limiting Uncertainty Relations in Laser-Based Measurements of Position and Velocity Due to Quantum Shot Noise." Entropy 21, no. 3 (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 measure

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11

Ritchie, Nicholas W. M. "Embracing Uncertainty: Modeling the Standard Uncertainty in Electron Probe Microanalysis—Part I." Microscopy and Microanalysis 26, no. 3 (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. Th

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12

Ritchie, Nicholas W. M. "Embracing Uncertainty: Modeling Uncertainty in EPMA—Part II." Microscopy and Microanalysis 27, no. 1 (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

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13

KOIKE, Masayoshi. "Expression of Uncertainty in Measuremnet. Evaluation Methods of Uncertainty in Measurement." Journal of the Japan Society for Precision Engineering 65, no. 7 (1999): 941–44. http://dx.doi.org/10.2493/jjspe.65.941.

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14

Giroud, C., J. Arnaud, and A. Vassault. "Uncertainty of measurement." Annales de biologie clinique 68, no. 1 (2010): 237–45. http://dx.doi.org/10.1684/abc.2011.0561.

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15

Hinrichs, Wilfried. "Uncertainty of Measurement." Materials Testing 36, no. 11-12 (1994): 476–80. http://dx.doi.org/10.1515/mt-1994-3611-1212.

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16

Busch, Paul, Pekka Lahti, and Reinhard F. Werner. "Measurement uncertainty relations." Journal of Mathematical Physics 55, no. 4 (2014): 042111. http://dx.doi.org/10.1063/1.4871444.

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17

Abernethy, R. B., R. P. Benedict, and R. B. Dowdell. "ASME Measurement Uncertainty." Journal of Fluids Engineering 107, no. 2 (1985): 161–64. http://dx.doi.org/10.1115/1.3242450.

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The purpose of this paper is to introduce the new ASME measurement uncertainty methodology which is the basis for two new ASME/ANSI standards and the ASME short course of the same name. Some background and history that led to the selection of this methodology are discussed as well as its application in current SAE, ISA, JANNAF, NRC, USAF, NATO, and ISO Standards documents and short courses. This ASME methodology is rapidly becoming the national and international standard.

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18

Dieck, Ronald H. "Measurement uncertainty models." ISA Transactions 36, no. 1 (1997): 29–35. http://dx.doi.org/10.1016/s0019-0578(97)00004-9.

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19

Meija, Juris. "Measurement uncertainty challenge." Analytical and Bioanalytical Chemistry 409, no. 10 (2017): 2497. http://dx.doi.org/10.1007/s00216-017-0210-4.

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20

Ellison, Stephen L. R. "Implementing measurement uncertainty for analytical chemistry: theEurachem Guidefor measurement uncertainty." Metrologia 51, no. 4 (2014): S199—S205. http://dx.doi.org/10.1088/0026-1394/51/4/s199.

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21

TANAKA, Kenichi. "Expression of Uncertainty in Measurement. Traceability and Uncertainty in Measurement." Journal of the Japan Society for Precision Engineering 65, no. 7 (1999): 945–48. http://dx.doi.org/10.2493/jjspe.65.945.

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22

Bittera, Mikulas, Jozef Hallon, Imrich Szolik, and Rene Hartansky. "Alternative Approach Leading to Reduction in Measurement Instrument Uncertainty of EMI Measurement." Measurement Science Review 23, no. 2 (2023): 64–71. http://dx.doi.org/10.2478/msr-2023-0008.

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Abstract Even in the field of electromagnetic compatibility, low measurement uncertainty means high measurement quality. Although there are standardized procedures for obtaining the uncertainty of such a measurement, which facilitate uncertainty estimation, modern approaches show further reduction possibilities. The paper presents an alternative approach to reducing measurement instrument uncertainty in the case of electromagnetic interference measurement based on many years of our experience and a large number of measurements in this field. In the paper, two different methods of uncertainty r

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23

Stefopoulos, Georgios, Stylianos Rigas, Panagiotis Tsirikoglou, and Anestis I. Kalfas. "Evaluation of pressure and species concentration measurement using uncertainty propagation." E3S Web of Conferences 345 (2022): 02008. http://dx.doi.org/10.1051/e3sconf/202234502008.

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This paper presents a probabilistic uncertainity evaluation method as described in the Guide to the Expression of Uncertainty in Measurements (GUM) and its application to probe measurements on pressure and fuel concentration. All sources of unceratinties are expressed as probability distributions. Consequently, the overall standard uncertainty of the quantity can be calculated using the Gaussian error propagation formula. The result of the uncertainty evaluation yields the most probable value of the measurand and describes its distribution in terms of rectangular (standard uncertainty) or gaus

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24

Dong, Chensong. "Uncertainty Analysis for Fiber Permeability Measurement." Journal of Manufacturing Science and Engineering 127, no. 4 (2005): 907–11. http://dx.doi.org/10.1115/1.2039947.

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An uncertainty study for fiber permeability measurement is presented in this paper. The sources of uncertainty were identified. This paper focuses on the instrument and environmental uncertainties. The parameter uncertainties of both unsaturated and saturated measurements were estimated based on instrument accuracy limitations and environmental influences. Their influences on the permeability uncertainty were investigated by uncertainty propagation and Monte Carlo simulation. The significant factors affecting the permeability measurement uncertainty were identified. The results show that (1) u

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25

Kaslis, Kyriakos, Samel Arslanagic, and Olav Breinbjerg. "Accurate and Fast Numerical Estimation of Pattern Uncertainty for Mechanical Alignment Errors in High-Accuracy Spherical Near-Field Antenna Measurements." Sensors 25, no. 13 (2025): 4227. https://doi.org/10.3390/s25134227.

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Every experimental measurement is affected by random and/or systematic error sources, causing the measurand to have an associated uncertainty quantified in terms of a confidence interval and confidence level. For high-accuracy spherical near-field antenna measurements, there are approximately 20 error sources whose individual contributions to the measurand uncertainty must be estimated for each antenna under test; thus, this uncertainty estimation is a required task in each measurement project. The error sources associated with the mechanical alignment of the antenna under test are of particul

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26

SICOE, Gina Mihaela. "Uncertainty of measurement -Important parameter for product conformity assessment." University of Pitesti. Scientific Bulletin - Automotive Series 30, no. 1 (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 uncer

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27

Vasilevskyi, Oleksandr. "Methodology for assessing the accuracy of a measuring instrument for the ion concentration using its measurement model." Acta IMEKO 14, no. 1 (2025): 1–10. https://doi.org/10.21014/actaimeko.v14i1.1938.

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To analyze the metrological characteristics of measuring instruments, it was proposed to expand the conversion equation into a Taylor series. The components of this series yield equations that describe the instrument’s sensitivity as well as its additive and multiplicative errors. Additionally, a mathematical model is introduced, allowing the conversion of these additive and multiplicative errors into measurement uncertainty. The proposed models were tested using a measurement model for ion concentration based on ion-selective electrodes. The measurement accuracy assessment methodology demonst

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28

Pillarz, Marc, Axel von Freyberg, Dirk Stöbener, and Andreas Fischer. "Gear Shape Measurement Potential of Laser Triangulation and Confocal-Chromatic Distance Sensors." Sensors 21, no. 3 (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 mea

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29

Coskun, Abdurrahman, Berrin Berçik İnal, and Muhittin Serdar. "Measurement uncertainty in laboratory medicine: the bridge between medical and industrial metrology." Turkish Journal of Biochemistry 44, no. 2 (2019): 121–25. http://dx.doi.org/10.1515/tjb-2019-0170.

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Abstract Uncertainty is an inseparable part of all types of measurements, that is, in metrology a measurement without uncertainty is not possible. Calculation of uncertainty increases the awareness of the certainty of measurement results. Reporting measurement uncertainty is mandatory in almost all industrial sectors but not in laboratory medicine. Test results without analytical uncertainty increases the diagnostic uncertainty, causing errors that could seriously affect patients health. To improve diagnostic certainty, we should calculate and upon request report measurement uncertainty to lab

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30

Venteris, E. R., and 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

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31

Heltzel, Robert, Derek Johnson, Mohammed Zaki, Aron Gebreslase, and Omar I. Abdul-Aziz. "Understanding the Accuracy Limitations of Quantifying Methane Emissions Using Other Test Method 33A." Environments 9, no. 4 (2022): 47. http://dx.doi.org/10.3390/environments9040047.

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Researchers have utilized Other Test Method (OTM) 33A to quantify methane emissions from natural gas infrastructure. Historically, errors have been reported based on a population of measurements compared to known controlled releases of methane. These errors have been reported as 2σ errors of ±70%. However, little research has been performed on the minimum attainable uncertainty of any one measurement. We present two methods of uncertainty estimation. The first was the measurement uncertainty of the state-of-the-art equipment, which was determined to be ±3.8% of the estimate. This was determine

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32

Zhu, Jiangmiao, Yifan Wang, Kejia Zhao, Yidi Wang, Chaoxian Fu, and Kaige Man. "Assessment of Measurement Uncertainty for S-Parameter Measurement Based on Covariance Matrix." Sensors 24, no. 11 (2024): 3668. http://dx.doi.org/10.3390/s24113668.

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S-parameters are widely used to detail the scattering parameters of radio frequency (RF) components and microwave circuit modules. The vector network analyzer (VNA) is the most commonly used device for measuring S-parameters. Given the multiple frequency points, complex values, and intricate uncertainty propagation involved, accurately assessing the uncertainty of S-parameter measurements is difficult. In this study, we proposed a new method for assessing S-parameter uncertainty based on the covariance matrices, tracing back to the nominal uncertainty of calibration standards. First, we analyz

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33

Farkas, G., and Á. Drégelyi-Kiss. "Measurement uncertainty of surface roughness measurement." IOP Conference Series: Materials Science and Engineering 448 (November 30, 2018): 012020. http://dx.doi.org/10.1088/1757-899x/448/1/012020.

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34

Mueller, Thomas, Andreas Poesch, and Eduard Reithmeier. "Measurement Uncertainty of Microscopic Laser Triangulation on Technical Surfaces." Microscopy and Microanalysis 21, no. 6 (2015): 1443–54. http://dx.doi.org/10.1017/s1431927615015330.

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AbstractLaser triangulation is widely used to measure three-dimensional structure of surfaces. The technique is suitable for macroscopic and microscopic surface measurements. In this paper, the measurement uncertainty of laser triangulation is investigated on technical surfaces for microscopic measurement applications. Properties of technical surfaces are, for example, reflectivity, surface roughness, and the presence of scratches and pores. These properties are more influential in the microscopic laser triangulation than in the macroscopic one. In the Introduction section of this paper, the m

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35

Machado, João P. Z., Gabriel Thaler, Antonio L. S. Pacheco, and Rodolfo C. C. Flesch. "Impact of Angular Speed Calculation Methods from Encoder Measurements on the Test Uncertainty of Electric Motor Efficiency." Metrology 4, no. 2 (2024): 164–80. http://dx.doi.org/10.3390/metrology4020011.

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The imperative need to advance the development of more efficient electric motors requires the meticulous measurement of small increments while minimizing the associated uncertainty in dynamometer tests. One of the key variables in such tests is the angular speed, which is typically obtained based on encoder measurements. This paper proposes a systematic measurement uncertainty assessment method based on the Guide to the Expression of Uncertainty for the two most widely used methods for angular speed measurement, namely, the frequency and period methods. In addition, the impact of the angular s

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36

ISHII, Yasushi. "Expression of Uncertainty in Measurement. Uncertainty on Measurement of Laser Frequency." Journal of the Japan Society for Precision Engineering 65, no. 7 (1999): 958–61. http://dx.doi.org/10.2493/jjspe.65.958.

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37

Shrestha, Rajesh R., and 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, no. 3 (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 (I

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38

Kristiansen, Jesper. "The Guide to Expression of Uncertainty in Measurement Approach for Estimating Uncertainty." Clinical Chemistry 49, no. 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 outli

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Milushev, George. "THE SOURCES OF UNCERTAINTY OF THE MEASUREMENT RESULT AS ELEMENTS OF THE MEASUREMENT PROCESS." Metrology and instruments, no. 2 (December 13, 2024): 01. https://doi.org/10.30837/2663-9564.2024.2.01.

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Research objective – to facilitate the detection and determination of the contributing components associated with the sources of uncertainty in measurements across the full range of aspects of calibration, testing and inspection and process control. In the paper, based on the concept of the duality of measurement process – measurement result, the five elements of the measurement process ware divided and classified as base sources of uncertainty. Some relations with other references with more or less structured classifications of the sources of measurement uncertainty are exampled. The scientif

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40

Zaytsev, Sergey V. "UNCERTAINTY ASSESSMENT AND TOOLS FOR OPTIMIZING REGIONAL TAX POLICY AND APPLYING A REGULARIZING BAYESIAN APPROACH." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/7, no. 146 (2024): 217–28. http://dx.doi.org/10.36871/ek.up.p.r.2024.05.07.025.

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Measurement uncertainty is a quantitative measure of the quality of measurement results, without which they cannot be compared with each other, with specified reference values or with a reference point. Uncertainty assessment is essential to ensure metrological traceability of measurement results and to ensure accuracy and reliability. In addition, measurement uncertainty should be taken into account whenever a decision is made based on measurement results, for example in acceptance/rejection or transmission, deviation processes. The purpose of this article is to consider the main aspects of u

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Vulevic, Branislav, Cedomir Belic, and Luka Perazic. "Measurement uncertainty in broadband radiofrequency radiation level measurements." Nuclear Technology and Radiation Protection 29, no. 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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Huang, Yubin, Xiong Zhang, Kaisi You, Jihong Chen, Hao Zhou, and Hua Xiang. "Drifted Uncertainty Evaluation of a Compact Machine Tool Spindle Error Measurement System." Machines 12, no. 10 (2024): 695. http://dx.doi.org/10.3390/machines12100695.

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The accurate measurement of spindle errors, especially quasi-static errors, is one of the key issues for the analysis and compensation of machine tool thermal errors in machining accuracy. To quantitatively analyze the influence of the measurement system’s own drift on the measurement results, a drifted uncertainty evaluation method of the precision instrument considering the time drift coefficient is proposed. This study also produced a high-precision compact spindle error measurement device (with a displacement measurement error of less than ±1.33 μm and an angular measurement error of less

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43

Bernstein, Johannes, and Albert Weckenmann. "Measurement uncertainty evaluation of optical multi-sensor-measurements." Measurement 45, no. 10 (2012): 2309–20. http://dx.doi.org/10.1016/j.measurement.2011.10.032.

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44

Ray, Jr., Elden F. "Measurement uncertainty in conducting environmental sound level measurements." Noise Control Engineering Journal 48, no. 1 (2000): 8. http://dx.doi.org/10.3397/1.2827978.

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45

He, Qin Shu, Shi Fu Xiao, and Xin En Liu. "Application of ANN and SVM for Uncertainty Quantification and Propagation." Advanced Materials Research 230-232 (May 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) a

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46

Prokopenko, Ludmila V., Nikolay N. Courierov, Alla V. Lagutina, et al. "Uncertainty in the measurement and evaluation of physical factors of non-ionizing nature." Russian Journal of Occupational Health and Industrial Ecology 63, no. 5 (2023): 327–35. http://dx.doi.org/10.31089/1026-9428-2023-63-5-327-335.

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In metrology, measurement uncertainty is an expression of the statistical variance of values attributed to a measured quantity.  All measurements are subject to uncertainty, and the measurement result is complete only when it is accompanied by data on the uncertainty associated with it. The scientists have considered the main provisions of the current regulatory and methodological documents on the problem of accounting for uncertainty values when measuring physical factors of a non-ionizing nature and evaluating their results. In particular, the fundamental in terms of the definition and

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47

Cecinati, Francesca, Antonio Moreno-Ródenas, Miguel Rico-Ramirez, Marie-claire ten Veldhuis, and Jeroen Langeveld. "Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data." Atmosphere 9, no. 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, mo

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48

Zakharov, Igor, Iryna Zadorozhna, Dariusz Świsulski, and Dimitar Diakov. "Accounting for the distributions of input quantities in the procedure for the measurement uncertainty evaluation when calibrating the goniometer." Ukrainian Metrological Journal, no. 1 (April 12, 2023): 34–38. http://dx.doi.org/10.24027/2306-7039.1.2023.282586.

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The discords concerning the measurement uncertainty evaluation in the Guide to the Expressing of Uncertainty in Measurement (GUM) and its Supplement 1 are considered. To overcome these discords, the authors of the paper propose to use the kurtosis method and the law of the propagation of the expanded uncertainty. Using the example of the goniometer calibration, the features of accounting for the distribution laws of input quantities in the procedure for the measurement uncertainty evaluation are shown. A model for direct measurements of the value of a reference measure of the angle using a gon

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Sandip Nehe. "Determination of Uncertainty in calibration of External Micrometer." Advances in Nonlinear Variational Inequalities 27, no. 3 (2024): 280–89. http://dx.doi.org/10.52783/anvi.v27.1373.

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In recent years there has been a growing awareness of measurement uncertainty, mainly for two reasons. First, the ever- increasing number of laboratory accreditations requires the evaluation of measurement uncertainty, especially in the area of calibration. Second, quality system protocols get mature with process and time. This is because manufacturers ensure the reliability of their measurements through correct calibration of their test and measuring equipment. International and national regulations require calibration and testing laboratories to provide result of measurement uncertainty. Cal

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Koj, Sebastian, Axel Hoffmann, and Heyno Garbe. "Measurement Uncertainty of Radiated Electromagnetic Emissions in In Situ Tests of Wind Energy Conversion Systems." Advances in Radio Science 16 (September 4, 2018): 13–22. http://dx.doi.org/10.5194/ars-16-13-2018.

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Abstract. The electromagnetic (EM) emissions of wind energy conversion systems (WECS) are evaluated in situ. Results of in situ tests, however, are only valid for the examined equipment under test (EUT) and cannot be applied to series production as samples, as the measurement uncertainty for in situ environment is not characterized. Currently measurements must be performed on each WECS separately, this is associated with significant costs and time requirement to complete. Therefore, in this work, based on the standard procedure according to the “Guide to the Expression of Uncertainty” (GUM, 20

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