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Metrology and Measurement Systems

The Journal of Committee on Metrology and Scientific Instrumentation of Polish Academy of Sciences

4 Issues per year


IMPACT FACTOR 2016: 1.598

CiteScore 2016: 1.58

SCImago Journal Rank (SJR) 2015: 0.554
Source Normalized Impact per Paper (SNIP) 2015: 1.363

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Online
ISSN
2300-1941
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In This Section
Volume 23, Issue 4 (Dec 2016)

An Algorithm for Improving the Accuracy of Systems Measuring Parameters of Moving Objects

Dimitar Dichev
  • Corresponding author
  • Technical University of Gabrovo, Faculty of Machine and Precision Engineering, Hadji Dimitar 4, 5300 Gabrovo, Bulgaria
  • Email:
/ Hristofor Koev
  • Technical University of Gabrovo, Faculty of Machine and Precision Engineering, Hadji Dimitar 4, 5300 Gabrovo, Bulgaria
  • Email:
/ Totka Bakalova
  • Technical University of Liberec, Institute for Nanomaterials, Advanced Technologies and Innovation, Studentska 2, 46117 Liberec, Czechia
  • Email:
/ Petr Louda
  • Technical University of Liberec, Department of Material Science, Studentska 2, 46117 Liberec, Czechia
  • Email:
Published Online: 2016-12-13 | DOI: https://doi.org/10.1515/mms-2016-0041

Abstract

The paper considers an algorithm for increasing the accuracy of measuring systems operating on moving objects. The algorithm is based on the Kalman filter. It aims to provide a high measurement accuracy for the whole range of change of the measured quantity and the interference effects, as well as to eliminate the influence of a number of interference sources, each of which is of secondary importance but their total impact can cause a considerable distortion of the measuring signal. The algorithm is intended for gyro-free measuring systems. It is based on a model of the moving object dynamics. The mathematical model is developed in such a way that it enables to automatically adjust the algorithm parameters depending on the current state of measurement conditions. This makes possible to develop low-cost measuring systems with a high dynamic accuracy. The presented experimental results prove effectiveness of the proposed algorithm in terms of the dynamic accuracy of measuring systems of that type.

Keywords: Kalman filter; adaptive algorithm; dynamic measurements; dynamic error; adaptive measuring systems

References

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About the article

Received: 2015-10-27

Accepted: 2016-04-10

Published Online: 2016-12-13

Published in Print: 2016-12-01



Citation Information: Metrology and Measurement Systems, ISSN (Online) 2300-1941, DOI: https://doi.org/10.1515/mms-2016-0041. Export Citation

© Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)

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