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Measurement System Based on Nonrecursive Filters with the Optimal Correction of the Dynamic Measurement Error

  • GENERAL ISSUES OF METROLOGY AND MEASURING EQUIPMENT
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Measurement Techniques Aims and scope

This article reviews the publications on the theory of dynamic measurements. The problem of minimizing the dynamic measurement error, whose components are due to the dynamic properties (inertia) of the sensor and additive noise at its output, is discussed. To solve this problem, a method is proposed for minimizing the dynamic measurement error as a result of the simultaneous correction of the specified components, and the structure of the measurement system is developed. The measurement system evaluates the dynamic measurement error and reduces it through a simultaneous restoration and filtering of the input measured signal of the sensor. The structure of a special filter with the preliminary correction of the transfer function of the sensor for the further processing of the measured signal is proposed. The processing of the dynamic measurement error consists of the iterative application of a finite impulse restoring filter (or nonrecursive filter) and estimation of the dynamic error. The computer simulation of the developed measurement system was performed for the second-order sensor. The optimal (in terms of the minimum estimate of the dynamic error) values of the order of the restoring filter for the input signals of various types in the presence of an additive Gaussian noise at the sensor output were obtained. The reduction of the dynamic error with the use of the developed measurement system is demonstrated. The obtained results can be used in measuring the parameters of rapidly varying processes when the dynamic component of the error is dominant, which is due to the dynamic properties (inertia) of the sensor and additive noise at its output.

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Notes

  1. Interstate standardization recommendations 29-2013. State System for Ensuring Uniform Measurement. Metrology. Basic terms and definitions.

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Acknowledgment

This work was supported by the Ministry of Education and Science of the Chelyabinsk Region within the regional project of the fundamental and applied scientific research No. 20-48-740022 r_a_Chelyabinsk "Regularization methods for processing noisy data in multichannel measuring systems."

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  1. South Ural State University (National Research University), Chelyabinsk, Russia

    A. S. Volosnikov

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Correspondence to A. S. Volosnikov.

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Translated from Izmeritel'naya Tekhnika, No. 10, pp. 19–25, October, 2022.

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Volosnikov, A.S. Measurement System Based on Nonrecursive Filters with the Optimal Correction of the Dynamic Measurement Error. Meas Tech 65, 720–728 (2023). https://doi.org/10.1007/s11018-023-02144-6

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