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Measuring system on a basis of non-recursive filters with optimal dynamic error correction
https://doi.org/10.32446/0368-1025it.2022-10-19-25
Abstract
The problem of the dynamic measurement error estimation and compensation is considered. This type of error is determined by two components. The fi rest one is due to dynamic properties (inertia) of a sensor. The second one is due to the presence of an additive noise at the sensor output. The dynamic error reduction consists in simultaneous correction of these two components. The structure of the measuring system with the dynamic measurement error estimation is developed. Correction of the dynamic error is carried out by simultaneous restoration and fi altering of the measured sensor input signal. The structure of a special filter with a preliminary correction of the sensor transfer function to a form convenient for further processing of the measured signal is proposed. Further signal processing consists in the iterative application of a restoring FIR fi later with the dynamic error estimation. A computer simulation of the proposed measuring system for the second-order sensor was carried out. Optimal (in the sense of minimization of the dynamic error estimation) orders of the restoring filter are obtained for input signals of various types in the presence of an additive Gaussian noise at the sensor output. A decrease in the dynamic error estimation based on the proposed structure of the dynamic measuring system is demonstrated. The application fi eld of the results obtained is the measurement of fast-changing processes, when the dynamic component of the error, caused by dynamic properties (inertia) of the sensor, as well as additive noises at its output, is dominant.
Keywords
sensor,
dynamic measurement,
optimal signal processing,
finite impulse response filters,
dynamic measurement error
Supporting agencies: the work was supported by the Ministry of Education and Science of the Chelyabinsk region within the framework of the regional project of fundamental and applied scientifi c research no. 20-48-740022 r_a_chelyabinsk “Regularization methods for processing noisy data in multichannel measuring systems”.
About the Author
A. S. Volosnikov
South Ural State University (National Research University)
Russian Federation
Russian Federation
Andrei S. Volosnikov
Chelyabinsk
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For citations:
Volosnikov A.S. Measuring system on a basis of non-recursive filters with optimal dynamic error correction. Izmeritel`naya Tekhnika. 2022;(10):19-25. (In Russ.) https://doi.org/10.32446/0368-1025it.2022-10-19-25
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