Estimating dynamic mechanical quantities and their associated uncertainties: application guidance

TL;DR

This paper provides practical guidance and software tools for estimating dynamic mechanical quantities and their uncertainties, addressing challenges in applying calibration data in industry.

Contribution

It introduces an approach for evaluating uncertainties in dynamic measurements, including deconvolution techniques, with implementation in accessible software.

Findings

Methods improve reliability of dynamic measurement estimates

Software facilitates practical uncertainty evaluation

Guidance aids industry application of calibration data

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.