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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) 2016: 0.460
Source Normalized Impact per Paper (SNIP) 2016: 1.228

Open Access
Online
ISSN
2300-1941
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Volume 24, Issue 1 (Mar 2017)

Comparison of Time Warping Algorithms for Rail Vehicle Velocity Estimation in Low Speed Scenarios

Stefan Hensel
  • 1) University of Applied Sciences Offenburg, Department for Electrical Engineering, Badstraße 24, D-77652 Offenburg, Germany
  • Email:
/ Marin B. Marinov
  • Corresponding author
  • 2) Technical University of Sofia, Faculty of Electronic Engineering and Technologies, Kliment Ohridski Blvd., BG-1756 Sofia, Bulgaria
  • Email:
Published Online: 2017-03-20 | DOI: https://doi.org/10.1515/mms-2017-0012

Abstract

Precise measurement of rail vehicle velocities is an essential prerequisite for the implementation of modern train control systems and the improvement of transportation capacity and logistics. Novel eddy current sensor systems make it possible to estimate velocity by using cross-correlation techniques, which show a decline in precision in areas of high accelerations. This is due to signal distortions within the correlation interval. We propose to overcome these problems by employing algorithms from the field of dynamic programming. In this paper we evaluate the application of correlation optimized warping, an enhanced version of dynamic time warping algorithms, and compare it with the classical algorithm for estimating rail vehicle velocities in areas of high accelerations and decelerations.

Keywords: velocity estimation; cross-correlation; dynamic programming; eddy current sensors

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About the article

Received: 2015-10-15

Accepted: 2016-09-24

Published Online: 2017-03-20

Published in Print: 2017-03-01


Citation Information: Metrology and Measurement Systems, ISSN (Online) 2300-1941, DOI: https://doi.org/10.1515/mms-2017-0012.

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© 2017 Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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