Abstract
Relationships characterizing measuring instruments are determined in a measuring experiment called calibration. The values of the parameters describing calibrated curves are measured with associated uncertainties. Identification of a given type of dependency is made based on the obtained values of the measured parameters. The most popular method of this identification is the least squares method, well implemented for polynomial relationships. In metrological practice, when identifying a non-linear calibrated relationship, it very often happens that increasing the polynomial degree within reasonable limits does not lead to a significant reduction of the approximation error. In that case, the primary dependence is transformed into a linear one by changing the variables. Then parameters of such a linearized relationship are determined by the least squares’ method. The article discusses the solution of estimating the uncertainty of parameters identified for the non-polynomial dependence, considering the instrumental uncertainties for the measured values.
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Zakharov, I., Neyezhmakov, P., Semenikhin, V., Warsza, Z.L. (2022). Measurement Uncertainty Evaluation of Parameters Describing the Calibrated Curves. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_38
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DOI: https://doi.org/10.1007/978-3-031-03502-9_38
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