E3S Web of Conferences (Jan 2023)

Development of a multi-channel classifier of rail line states

  • Tarasov Evgeny,
  • Tarasova Anna,
  • Zolkin Alexander,
  • Kunygina Liliya,
  • Burakova Anzhelika

DOI
https://doi.org/10.1051/e3sconf/202341101020
Journal volume & issue
Vol. 411
p. 01020

Abstract

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The article deals with the construction of a three-channel invariant classifier that has the properties of classifying the states of rail lines into a set of classes that are invariant to changes in the longitudinal resistance of the rail line and the transverse conductivity of the insulation of the ballast material. Invariance is achieved taking into account the change in the transverse conductivity of the insulation and the longitudinal resistance of the rail line while compiling systems of equations of state for rail lines, which are the decisive functions of the classifier. The article shows that the three-channel method allows for the correct recognition of all three classes of rail line states by three decision functions with arguments - voltages and currents at the input and output of the rail line. The block diagram of the operation algorithm of the three-channel classifier of the states of the rail lines allows to form the recognition process and the majority classification depending on the states of the channels. The feasibility of the algorithm is confirmed by simulation studies on a mathematical model and graphical results.