Abstract
Recently several European National Measurement Institutes have established traceable calibration methods for dynamic mechanical quantities, e.g. dynamic force, torque and pressure. However, the use in industry and elsewhere of dynamic calibration information provided on certificates is not straightforward. Typically it is necessary to employ deconvolution techniques to obtain estimates of measurands, and the deconvolution method itself and the associated algorithms are sources of uncertainty that must be included in uncertainty budgets. There is a need for practical guidance for end users on how to use the newly-available dynamic calibration information. To this end we set out an approach to the evaluation of uncertainties associated with dynamic measurements that we believe covers the most relevant cases. The methods have been embodied in publicly-available software and we show how they can be used to tackle some example problems. We believe that the methods lead to more reliable estimates of the relevant measurands and their associated uncertainties.
Highlights
Many applications of the measurement of quantities such as force, torque and pressure are dynamic, i.e., the measurand shows a strong variation over time
It is appropriate for a wide range of applications and all the examples discussed in this paper are modelled as linear time-invariant (LTI) systems
The analysis and characterization of dynamic measurements is a topic of growing importance and a large amount of literature exists for the mathematical modelling and for the evaluation of uncertainties
Summary
Many applications of the measurement of quantities such as force, torque and pressure are dynamic, i.e., the measurand shows a strong variation over time. European collaborative projects [1, 2] provided outputs in the forms of general dynamic models for the complete calibration measurement chain, methods for uncertainty evaluation in line with uncertainty evaluation for static measurements, and general procedures for correcting measurements for dynamic effects. These outputs have not yet been embodied in documentary standards and international guidance documents or in software that can be used in industrial applications to correct measurements and provide uncertainty evaluations that are compliant with the ’Guide to the expression of uncertainty in measurement’ (GUM) [3]. Readers who require an introduction to deconvolution methods in metrology are referred to [4]
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