On challenges in the uncertainty evaluation for time-dependent measurements

Published

June 14, 2016

Author(s)

Sascha Eichstadt, Volker Wilkens, Andrew Dienstfrey, Paul D. Hale, Ben Hughes, Charles Jarvis

Abstract

The measurement of quantities with time-dependent values is a common task in many areas of metrology. Although well established techniques are available for the analysis of such measurements, serious scientific challenges remain to be solved to enable their routine use in metrology. In this contribution we focus on the challenge of estimating a time-dependent measurand when the relationship between the value of the measurand and the indication is modeled by a onvolution. Mathematically, deconvolution is an ill-posed inverse problem, requiring regularization to stabilize the inversion in the presence of noise. We present and discuss deconvolution in three practical applications: thrust-balance, ultra-fast sampling oscilloscopes and hydrophones. Each case study takes a different approach to modeling the convolution process and regularizing its inversion. Critically, all three examples lack the assignment of an uncertainty to the influence of the regularization on the estimation accuracy. To this end, we discuss several approaches which can serve as starting point for future developments in metrology.

Citation

Metrologia

Pub Type

Journals

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Keywords

metrology, dynamic measurements, deconvolution, regularization

Citation

Eichstadt, S. , Wilkens, V. , Dienstfrey, A. , Hale, P. , Hughes, B. and Jarvis, C. (2016), On challenges in the uncertainty evaluation for time-dependent measurements, Metrologia, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=919437 (Accessed December 13, 2024)