Computer Implementation of Algorithmic Components of Redundant Measurement Methods

This article demonstrates the implementation of the proposed algorithm for computer modeling of redundant measurement methods to solve problems to improve the accuracy of measurements of a controlled quantity with a nonlinear and unstable transformation function. Improving accuracy is achieved by processing the results of redundant measurements which are an array of data according to the proposed measurement equations. In addition, the article presents the possibility of determining the time variation of the parameters of the transformation function. A comparative analysis of the results of computer simulation of redundant and direct methods with unstable parameters of the linear and nonlinear sensor transformation functions is carried out. It was proved that, in the case of an increase in deviations of the parameters of the transformation function from the nominal values, the use of redundant methods provides a significantly higher measurement accuracy compared to direct methods. This became possible due to the automatic elimination of the systematic component of the error of the measurement result due to a change in the parameters of the transformation function under the influence of destabilizing factors. It was also found that, in contrast to direct methods, methods of redundant measurements allow working with a nonlinear transformation function without additional linearization or dividing it into linear sections, which also contributes to increased accuracy. In general, the application of the proposed approach in the modeling system proves its effectiveness and feasibility. Thus, there is reason to argue about the prospects of redundant measurements in the field of improving accuracy with a nonlinear and unstable transformation function, as well as the possibility of identifying deviations of the parameters of the transformation function from their nominal values.