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Measurement Uncertainty in the Calibration of Low‐flow Ambient Air Samplers
Author(s) -
Wulff Shaun S.,
Weitz Mark A.
Publication year - 2005
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.678
Subject(s) - calibration , measurement uncertainty , observational error , statistics , ordinary least squares , linear regression , uncertainty analysis , flow (mathematics) , mathematics , set (abstract data type) , airflow , econometrics , environmental science , computer science , engineering , geometry , mechanical engineering , programming language
This paper considers the quality of measurement for a new standard used to assess ambient airflow measurements. The quality is quantified through the uncertainty associated in the measurements of this device. While guidelines are available for these analyses, this case study presents a set of additional challenges since the flow rate measurements are based on a linear relationship between two functions where the variables making up these functions are measured with non‐negligible error. In order to estimate the parameters describing this linear relationship, it is necessary to account for the variability associated with these errors. Measurement error modeling approaches can be used to estimate the linear regression parameters and the associated uncertainties. Ordinary least squares procedures are simpler, but must be used with care since the estimates can be biased and the resulting uncertainties can be underestimated. Once estimates for the linear relationship are obtained, measurements from the device are used to calculate a predicted flow rate. Techniques are presented for estimating the uncertainty associated with this predicted flow rate. Copyright © 2005 John Wiley & Sons, Ltd.

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