Classification of rail line conditions using pattern recognition principles

This article examines the question of how to classify rail line conditions using pattern recognition methods. An analysis of the track circuit measurement channel, which serves as the primary source of information about the track condition, is conducted. Three main conditions are identified: operational, occupied, and faulty. The article describes in detail the structure of the classifier and considers five operating modes of the track circuit: normal, shunt, control, as well as equipment diagnostic modes at the feeding and relay ends. The main parameters that influence the classification are identified as the voltage and current at the input of the classifier's decision-making device. These parameters depend on the characteristics of the signal source, primary parameters of the rail line, and, in the case of shunt and control modes, on the position of the train and the condition of the rail line. The authors consider the task of forming informative features to improve classification efficiency and propose a simple decision rule for separating classes of conditions, illustrating it with a geometric interpretation. The article is dedicated to the development of an automatic classification system for rail line conditions based on pattern recognition principles, with an emphasis on identifying informative features and synthesizing decision functions.