Processing of Measurement Results for Mechanical Values by Intellectual Equipment Systems (Uncertainty Conditions)
Abstract views: 67
PDF Downloads: 70



mechanical values, error, uncertainty of measurement, mean square deviation

How to Cite

Kvasnikov, V., Perederko, A., Kuzmich, L., & Kotetunov, V. (2019). Processing of Measurement Results for Mechanical Values by Intellectual Equipment Systems (Uncertainty Conditions). Metrology and Instruments, (4), 34-38.


This article is devoted to the measurement of mechanical quantities. The proposed methods are directed to the mechanical values of the intellectual devices of the system (in conditions of uncertainty). At the present stage of the development of intellectual systems, the issue of creating methods for rapid processing of the obtained results, determining the accuracy of their measurement in real time, in particular in solving management problems and making decisions under uncertainty, remains an issue.

The result of the measurement of mechanical quantities, in particular the cost of thermal energy by intelligent instrumentation systems (IPS), is complete, provided that it is accompanied by an estimate of its accuracy [1]. The processing accuracy of the measurement results depends on the type of measurement, the number of experimental data, the accuracy requirements of the measurement, and so on. Only during direct one-time measurements the result of the study may be the result of the measurement (provided that the systematic errors of measurement are not corrected). In other measurements, processing can be done using standardized techniques (eg statistical methods), or require the creation of special algorithms.

In general, the processing involves the following steps [2, 3, 4]:

  • preliminary analysis of the results of observations (primary measurements), their systematization of the rejection of obviously false results;
  • Correction of the influence of systematic effects (study of mea­surement conditions, calculation and amendment);
  • analysis of the effects of random effects, testing hypotheses about their distribution, selection of the best estimates of the required values;
  • evaluation of the accuracy characteristics of a numerical algorithm, its stability;
  • execution of calculations in accordance with the chosen algorithm;
  • analysis of the results;
  • submission of measurement results and characteristics of their accuracy in the appropriate form.

Each type of measurement has its own characteristics and therefore the specific content of these operations of processing the results of a particular type of measurement has certain differences. The approaches to processing the results of measurement of mechanical quantities by intelligent instrumental systems, in particular estimating the accuracy of measurements under uncertainty, are substantiated.
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.