Comparison of the Gum and Monte Carlo Methods for the Uncertainty Estimation in Electromagnetic Compatibility Testing

Azpúrua, Marco A.; Tremola, C.; Barrios, Eduardo Paez

doi:10.2528/pierb11081804

Cited by 31 publications

(32 citation statements)

References 8 publications

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“…In 2008, the Joint Committee on Measurement Guidelines introduced a supplemental document. The Monte Carlo method (MCM) was used to assess measurement uncertainty [11][12][13]. According to the supplementary document, measurement uncertainty with the MCM is newly issued in China, which provides a method for assessing the uncertainty of measurement, thus broadening the application scope of uncertainty assessment.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty analysis of dynamic thermal rating based on environmental parameter estimation

Wang¹,

Tao²,

Yan³

et al. 2018

J Wireless Com Network

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Dynamic thermal rating (DTR) of transmission lines is related to wind speed, wind direction, ambient temperature, and so on. Among the environmental parameters, there is a difference between the obtained environmental parameters and the true value. Therefore, only the deterministic values of environmental parameters and DTR are not accurate enough. Considering the environmental parameters obtained with uncertainty, the uncertainty of environment parameters based on Monte Carlo Method (MCM) is studied in this paper. According to the heat balance equation of transmission lines, the uncertainty analysis of transmission line ampacity is realized based on CIGRE standard. The best estimation value, standard uncertainty, and confidence interval are obtained under a given confidence level of environmental parameters. The experimental results show that DTR can fully improve the transmission capacity of transmission lines, and MCM is an effective method to assess uncertainty of DTR.

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Section: Introductionmentioning

confidence: 99%

Uncertainty analysis of dynamic thermal rating based on environmental parameter estimation

Wang¹,

Tao²,

Yan³

et al. 2018

J Wireless Com Network

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show abstract

“…Especially for the complex or non-linear measurement model, it is very difficult to calculate the transfer coefficient and investigate the correlation between the inputs based on the GUM method, the evaluation staff needs professional knowledge about uncertainty evaluation, and extensive assessment experience [6], [7]. However, it is a practical method to evaluate uncertainty based on statistics by computer simulation [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Modeling and Evaluation of CMM Task Oriented Measurement Based on SVCMM

Chen

Cheng

et al. 2017

Measurement Science Review

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Due to the variety of measurement tasks and the complexity of the errors of coordinate measuring machine (CMM), it is very difficult to reasonably evaluate the uncertainty of the measurement results of CMM. It has limited the application of CMM. Task oriented uncertainty evaluation has become a difficult problem to be solved. Taking dimension measurement as an example, this paper puts forward a practical method of uncertainty modeling and evaluation of CMM task oriented measurement (called SVCMM method). This method makes full use of the CMM acceptance or reinspection report and the Monte Carlo computer simulation method (MCM). The evaluation example is presented, and the results are evaluated by the traditional method given in GUM and the proposed method, respectively. The SVCMM method is verified to be feasible and practical. It can help CMM users to conveniently complete the measurement uncertainty evaluation through a single measurement cycle.

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“…Its latest edition [5], which contains minor corrections, is the first edition published under the Charter of the Joint Committee on Guides in Metrology (JCGM). The same year a "Supplement 1 to the 'Guide to the Expression of Uncertainty in Measurement' -Propagation of Distributions using a Monte Carlo Method" [6] was published; in this supplement a numerical technique for evaluating uncertainty based on the Monte Carlo method (GUMS1) is described, which has been applied in several areas other than nonionizing radiation safety [7,8].…”

Section: Introductionmentioning

confidence: 99%

Application of the Monte Carlo Method for the Estimation of Uncertainty in Radiofrequency Field Spot Measurements

Iakovidis

Apostolidis

Samaras

2015

Measurement Science Review

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The objective of the present work is the application of the Monte Carlo method (GUMS1) for evaluating uncertainty in electromagnetic field measurements and the comparison of the results with the ones obtained using the 'standard' method (GUM). In particular, the two methods are applied in order to evaluate the field measurement uncertainty using a frequency selective radiation meter and the Total Exposure Quotient (TEQ) uncertainty. Comparative results are presented in order to highlight cases where GUMS1 results deviate significantly from the ones obtained using GUM, such as the presence of a non-linear mathematical model connecting the inputs with the output quantity (case of the TEQ model) or the presence of a dominant nonnormal distribution of an input quantity (case of U-shaped mismatch uncertainty). The deviation of the results obtained from the two methods can even lead to different decisions regarding the conformance with the exposure reference levels.

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Comparison of the Gum and Monte Carlo Methods for the Uncertainty Estimation in Electromagnetic Compatibility Testing

Cited by 31 publications

References 8 publications

Uncertainty analysis of dynamic thermal rating based on environmental parameter estimation

Uncertainty analysis of dynamic thermal rating based on environmental parameter estimation

Uncertainty Modeling and Evaluation of CMM Task Oriented Measurement Based on SVCMM

Application of the Monte Carlo Method for the Estimation of Uncertainty in Radiofrequency Field Spot Measurements

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