• Journal of the Korea Society of Computer and Information
• /
• v.8 no.4
• /
• pp.165-175
• /
• 2003

The concept of measurement uncertainty has been recognised for many years since "Guide to the Expression of Uncertainty in Measurement" was published 1993 by ISO. This study firstly propose the mathematical model to evaluate uncertainty considering the dispersion of samples because the mathematical model of a measurement is an important to evaluate uncertainty, and it must contains every quantify which contribute significantly to uncertainty in the measurement result. Secondly the standard uncertainty of the result of a measurement, namely combined standard uncertainty is evaluated using the law of propagation of uncertainty, what is termed in GUM method. In GUM method, a measurand is usually approximated by a linear function of its variables by the transforming its input quantities. Furthermore central limit theorem is applied to the input quantity. However the mathematical model of a measurement is generally not always a linearity function, and a distribution function of input or output quantity is not necessarily normal distribution. Then, in some cases GUM method is not favorable to evaluate a measurement uncertainty. Therefore this study propose a new method and its algorithm which use the Monte-carlo simulation to evaluate a measurement uncertainty in both case of linearity or non-linearity function. function.

• Proceedings of the KSR Conference
• /
• 2003.10c
• /
• pp.301-306
• /
• 2003

Recently, uncertainty of measurement became a major concern for the people working on the laboratory evaluation and accreditation. 'uncertainty of measurement is a parameter associated with the result of a measurement that characteristics the dispersion of the value that could reasonably be attributed to the measured.' This study analysed how to estimate uncertainty of measurement in mechanical characteristic exam for Plastic material. its uncertainty was estimated according to International Organization for Standardization(ISO), they were named to A type uncertainty, B type uncertainty, combined standard uncertainty, and expanded uncertainty. We obtained that the combined standard uncertainty was 0.96697 MPa and the expanded uncertainty was 2.291MPa.

• 유체기계공업학회:학술대회논문집
• /
• 2002.12a
• /
• pp.354-359
• /
• 2002

The new piston prover was developed and the flow measurement uncertainty of this piston prover was evaluated according to ISO/IEC 17025. The laser interferometer was employed to measure accurately the testing time. Uncertainty was calculated with evaluation of various uncertainty factors affected in flow measurement. The expanded uncertainty(U) of the piston Over was $1.3{\times}10^{-3}$ (at the confidence level of $95\%$). This evaluation example will be useful in flow measurement uncertainty determination of other gas flow measurement system.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.27 no.12
• /
• pp.1758-1765
• /
• 2003

Monte Carlo simulation(MC) method was used as an uncertainty assessment tool for gas flow measurement in this paper. Uncertainty sources for gas flow measurement were analyzed, and probability distribution characteristics of each source were discussed. Detailed MC methodology was described including the effect of the number of simulation. The uncertainty result was compared with that of the conventional sensitivity coefficient method, and it was revealed that the results were different from each other for this particular gas flow measurement case of which the modelling equation was nonlinear. The MC was comparatively simple, convenient and accurate as an uncertainty assessment method, especially in cases of complex, nonlinear measurement modelling equations. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the measurement.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.4
• /
• pp.91-99
• /
• 2009

Because of both precise measurement and efficient quality control, coordinate measuring machines(CMMs) have been widely used in the industry. The purpose of this paper is to present a method to estimate the CMM measurement uncertainty using design of experiments. A factorial design is applied to carry out the performance test proposed by ISO 10360 and to investigate CMM measurement errors associated to orientation and length of the length bar. In order to assess the measurement uncertainty for the performance test, an analysis of the uncertainty components that make up the uncertainty budget has been carried out. The procedure for evaluating the uncertainty of it follows GUM ("Guide to the expression of uncertainty in measurement"). The results show that the proposed method is suitable to investigate CMM performance and determine the contribution of machine variables to measurement uncertainty.

• Bulletin of the Korean Chemical Society
• /
• v.35 no.4
• /
• pp.1057-1060
• /
• 2014

In our previous articles, an approach has been proposed for the evaluation of the uncertainty of overall result from multiple measurements. In the approach, uncertainty sources were classified into two groups: the first including those giving same 'systematic' effect on each individual measurement and the second including the others giving 'random' effect on each individual measurement and causing a variation among individual measurement results. The arithmetic mean of the replicated measurements is usually assigned as the value for the overall result. Uncertainty of the overall result is determined by separately evaluating and combining an overall uncertainty from sources of the 'systematic' effect and another overall uncertainty from sources of the 'random' effect. This conceptual approach has been widely adopted in chemical metrology society. In this study, further logical proof with more detailed mathematical expressions is provided on the approach.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.4
• /
• pp.40-45
• /
• 2010

Evaluation of uncertainty is an ongoing process that can consume time and resources. It can also require the service of someone who is familiar with data analysis techniques. Therefore, it is important for laboratory personnel who are approaching uncertainty analysis for the first time to be aware of the resources required. International inclination of measurement filed to guarantee the traceability and confidence of measurement results discards the error concept and instead analyzes the measurement uncertainty. In this paper, we analyzed the elements of measurement uncertainty on surface roughness test which are the important things in mechanical parts test. Repeat the test by 3 men, the measurement uncertainty could be calculated.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.24 no.3
• /
• pp.18-30
• /
• 2020

This study deals an estimation method of thrust measurement uncertainty in solid rocket motors. Guidelines of the force measurement uncertainty estimation have been provided by ISO, domestic and international organizations. However, all of them are described by focusing on the force calibration machines and force transducers with a conceptually-driven way. Thus the guidelines cannot be directly applicable to uncertainty estimation of calibration equation and its linear approximation, which are critical error sources in the thrust measurement. In this paper, the equations taking into account effects of both error sources are derived based on fundamental concepts of measurement uncertainty. These are applied to the real thrust measurement system where a relatively simple estimation method for the thrust measurement uncertainty is proposed.

• Economic and Environmental Geology
• /
• v.37 no.1
• /
• pp.49-59
• /
• 2004

The concectration and distribution of contaminants obtained from a contaminated land investigation or an environmental geochemistry survey constitutes the basis of a decision-making process on environmental policies or of scientific researches. As the quality of data determines the reliability of the result, the investigation plan should be adjusted according to the purpose of the investigation. In general, the effort to improve the data quality had been focused mainly on the QA/QC procedures in laboratories. The rapid progress of analytical instrument has also contributed toward improving the analytical precision to a sacrificable degree. Nevertheless, in many cases, it is not the analytical precision that needs improvement for the better precision of overall measurement process: it is rather during the sampling process in the field that is responsible for the poor precision. To assess the data quality on a measured value, ISO recommends to provide information on "measurement uncertainty" along with the measured value. The measurement uncertainty in an environmental measurement context can be explained as the statistical number that expresses the degree of the uncertainty stemming from the sampling and analytical procedures. There is a cost involved in order to improve the precision of sampling and analytical methods so as to decrease the degree of measurement uncertainty. The economical point of compromise in an investigation planning can be achieved when the allowable degree of uncertainty has been set before-hand. The investigation can then be planned accordingly not to exceed the uncertainty limit. Furthermore, if the measurement uncertainty estimated from the preliminary investigation can be separated into sampling and analytical uncertainties, it can be used as a criterion where the resources for the investigation should be allotted cost-effectively to reinforce the weakest link of the whole investigation process. This paper aims to present a method of estimating the level of measurement uncertainty of a measured contamination concentration at a site used as an example and to show how the estimated uncertainty can be applied to serve the particular purpose of an investigation.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.25 no.12
• /
• pp.1898-1904
• /
• 2001

Measurement uncertainty should be evaluated according to ISO/IEC 17025. In Flow measurement area, uncertainty evaluation scheme was applied to the reference flow meter, sonic nozzle. Uncertainty was calculated by evaluating various uncertainty factors affected in flow measurement. The expanded uncertainty(U) of the sonic nozzle was 2.1$\times$ 10$^{-3}$ (confidence level of 95 %). This evaluation example will be useful in flow measurement uncertainty determination of other flow meters.