Analysis of interlaboratory comparisons affected by correlations of the reference standards and drift of the travelling standards

Bergoglio, M.; Malengo, Andrea; Mari, D.

doi:10.1016/j.measurement.2011.05.012

Cited by 11 publications

(10 citation statements)

References 4 publications

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“…The UMTS as pilot laboratory has performed repeated measurements over the duration of the KC in order to monitor the stability of the TS and also the correction to compensate the drift can be evaluated. The evaluated correction which depends on both the stability of the TS and the long term stability of the measurements and its standard uncertainty will be included in the model describing the measurement process of the KC [16]. The different approaches for evaluation drift effect to the COOMET.EM-K5 KC were applied [17].…”

Section: Behaviour Of the Travelling Standardmentioning

confidence: 99%

Main Results of COOMET.EM-K5 Key Comparison of Power

Velychko¹,

Karpenko²

2019

Ukrainian Metrological Journal

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the linking process between CCEM-K5 Key Comparison and COOMET.EM-K5 Key Comparison due of participating in CCEM-K5 Key Comparison. The paper is devoted to the discussion of issues concerning the participation and further evaluation of measurement data of COOMET.EM-K5 Key Comparison of Power. Main results of participating laboratories measuring the same power of travelling standard of low-frequency 50/60 Hz power in a framework of COOMET.EM-K5 Key Comparison of Power are presented. Besides, the paper describes some problems concerning the evaluation of travelling standard drift effect and its further influence on evaluation of Key Comparison Reference Value during a Key Comparison. Degrees of Equivalence and Expanded Uncertainties of National Metrology Institutes participants are set. In addition, E n number was calculated for each National Metrology Institute participating in COOMET.EM-K5 Key Comparison of Power with the aim of determining data consistency.

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Section: Behaviour Of the Travelling Standardmentioning

confidence: 99%

Main Results of COOMET.EM-K5 Key Comparison of Power

Velychko¹,

Karpenko²

2019

Ukrainian Metrological Journal

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“…The evaluated correction which depends on both the stability of the TS and the long term stability of the measurements and its standard uncertainty will be included in the model describing the measurement process of the KC [10]. I applied the different approaches for evaluation drift effect to the COOMET.EM-K5 KC [9].…”

Section: Evaluation Of the Travelling Standard's Drift Effectmentioning

confidence: 99%

Features of evaluation drift effect during Key Comparison COOMET.EM-K5

Karpenko¹

2017

Ukrainian Metrological Journal

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Results of pilot laboratory and participating laboratories which are measuring the same travelling standard during Key Comparison must be most similar. However, this may not always be possible, because the travelling standard which is sent in turn to all participating laboratories is not always perfectly stable. So that it is necessary to take into account the drift effect of the travelling standard. The article describes some problems concerning the evaluation drift effect of travelling standard and its further influence on evaluation key comparison reference value during Key Comparison. The procedure for evaluation drift effect when its model can be linear or not linear was presented. Comparative analysis of the proposed procedures for evaluation drift effect is applied to the Key Comparison of Power COOMET.EM-K5 was done.

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“…It can be proved (Appendix A) that covariances can be estimated by the following formula: (5) where each influence quantity l, l = 1…m is considered, if the influence quantity affects both Xi and Xj in the same direction, and = −1 in the opposite case. Moreover,  l is the fraction of LO variance of l on Xi and Xj (Appendix A), and wi,l and wi,j are the relative weights with which the influence quantity l affects the total uncertainty on Xi and Xj, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Several examples can be found in the literature, where covariances play a significant role in the evaluation of the combined standard uncertainty, including, but not limited to, interlaboratory comparisons [5], system identification [6], sensor data fusion [7], and vision-based measurements [8]. These same examples show that covariances are not always easy to detect and evaluate, and strict mathematical methods to evaluate them, although available [9], [10], are often complex to apply and time consuming.…”

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confidence: 99%

Covariance evaluation by means of uncertainty assessment

Dubois¹,

Leblond²,

Pou

et al. 2016

IEEE Instrum. Meas. Mag.

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One of the key points in modern measurement science is the evaluation of measurement uncertainty, according to the definition given by the International Vocabulary of Metrology (VIM) [1] and the procedure recommended by the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements [2]-[4]. According to these documents, when several sources of uncertainty are present, the related standard uncertainties shall be quadratically combined, and the covariances must be considered, if present [2]

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Analysis of interlaboratory comparisons affected by correlations of the reference standards and drift of the travelling standards

Cited by 11 publications

References 4 publications

Main Results of COOMET.EM-K5 Key Comparison of Power

Main Results of COOMET.EM-K5 Key Comparison of Power

Features of evaluation drift effect during Key Comparison COOMET.EM-K5

Covariance evaluation by means of uncertainty assessment

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