Mental Experiment in Metrology and Representation of Measurement Uncertainty in a Complex Form

• Main Author: V. Chalyy
• Format: Article
• Language: English
• Published: LLC Production and Commercial Company «FAVOR, LTD» 2018-10-01
• Series: Метрологія та прилади
• Subjects: measurement, uncertainty of measurement, metrology, concept GUM, mental experiment, real experiment, standard deviation, apparent uncertainty, real uncertainty, total uncertainty.
• Online Access: https://mmi-journal.org/index.php/journal/article/view/31
• ISSN: 2307-2180; 2663-9564

The essence of the thought experiment and its use in metrology for evaluating and presenting measurement results are studied. An imaginary experiment has a hypothetical-deductive structure, carried out on the basis of the developed program, plan-scheme, is based on experience and is based on the real laws of the phenomena under study and does not go beyond the boundaries of empirical preconditions. The term «uncertainty» of measurement is considered in three aspects: quantitative knowledge of objects of the real world, the technical procedure for obtaining pragmatic measurement information, evaluation of the measured information for making informed decisions and risk management. An analyzed of the shortcomings of exis­ting methods to assess the components of measurement uncertainty, based on the specific features of the GUM concept. In this concept, all components of measurement uncertainty are grouped abstractly into two categories - A and B without sufficient justification of the classification criteria. A method for classifying the components of uncertainty based on a real or mental experiment is proposed, and the results obtained are referred to as real (standard) uncertainty «and» imagi­nary (standard) uncertainty». The total uncertainty is considered as a complex value and is calculated on the basis of orthogonal vectors of the results of real and imaginary experiments. The proposed interpretation of the uncertainty of measurement gives a better understan­ding of the nature of uncertainty, simplifies entries and calculations.