Systematic approach to the modelling of measurements for uncertainty evaluation

Abstract

Modern evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the (input) quantities which influence the result of measurement. The knowledge about the input quantities is represented by means of appropriate probability density functions (pdfs), whereas the knowledge about the measurement process is expressed by a so-called model equation which reflects the interrelation between the measurand and the input quantities. The assignment of a pdf for a quantity is based on sound theory but there is no theory on modelling. Neither the Guide to the Expression of Uncertainty in Measurement nor other relevant uncertainty documents provide any guidance on systematic modelling. This paper proposes a systematic and versatile modelling concept that has evolved from the idea of the classical measuring chain. From this concept, a systematic procedure for modelling of measurements has been derived which is structured into five fundamental work steps and requires three types of standard modelling components. The concept utilizes only a few generic model structures which are strongly related to the method of measurement employed. These generic model structures can easily be tailored to any particular measurement task. The paper provides the theoretical reasoning for this concept and derives practical procedures for its application.