Abstract

The studies of the capabilities of redundant measurement methods revealed the high efficiency of the presented methods in increasing the accuracy of multiple measurements. It was proved that redundant measurement equations ensure the independence of the measurement result from the parameters of the transformation function and their deviations from the nominal values. Experimental studies have confirmed that the accuracy of multiple measurements is increased by processing the results of intermediate measurements using equations of redundant measurements by two approaches. In particular, it was found that processing the results of multiple measurements with the logarithmic transformation function with the first approach provides the value of the relative error of 0.75×10 %, and the second – 0.02×10.This suggests that the increase in accuracy is due to the total effect of the elimination of the systematic error component due to changes in the parameters of the transformation function and reduction of the random error component. The latter, in particular, concerns the algorithms for processing multiple measurements by two approaches. A comparative analysis was made, the advantages and disadvantages of each of the two approaches were determined. It was found that the second approach is less sensitive to an increase in the difference between the values of the controlled and normalized quantities. This allows us to state the possibility of measuring the controlled parameter of a large value without imposing high requirements on the power of the calibrated radiation source.There is reason to assert about the promising development of redundant measurement methods in the processing of the results of multiple measurements in the field of increasing accuracy with the nonlinear transformation function

Highlights

  • Modern industrial development poses urgent tasks for scientists and engineers to improve measurement accuracy and obtain reliable information while reducing the cost of metrological support

  • Mathematical models of multiple measurements with the logarithmic transformation function by two approaches, 6/4 ( 108 ) 2020 which describe the state of the measuring channel in time, were developed

  • These features in data processing will be manifested in a high-accuracy result by reducing the random error component and eliminating the influence of the systematic error component caused by the instability of the transformation function (TF) parameters

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Summary

Introduction

Modern industrial development poses urgent tasks for scientists and engineers to improve measurement accuracy and obtain reliable information (about the controlled parameter or object of study) while reducing the cost of metrological support. This task is especially acute when performing technological processes, such as in the chemical or textile industry. Particular attention should be paid to the industries and processes where long-term multiple measurements are needed to control the measuring parameter (quantity) within the tolerance With such a long-term measurement control under the influence of the environment, the parameters of the sensor transformation function change, which affects the accuracy of the measurement result [4] and, as a consequence, product quality. Studies aimed at improving the accuracy of multiple measurements with the nonlinear transformation function should be considered relevant

Literature review and problem statement
The aim and objectives of the study
Results of computer simulation of two approaches
Findings
Conclusions
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