Tree-based diagnostic classificators of hump retarders

Abstract

Tree-based diagnostic classificators of hump retarders

Panasov V.L., Nechitaylo N.M.

Incoming article date: 05.04.2025

The paper addresses the problem of the technical diagnostics of hump control devices, such as wagon retarders. The current analytical methods of monitoring and technical diagnostics of wagon retarder conditions are reviewed. The factors that are used in the existing diagnostics systems are analyzed and new factors to be taken into account, including specific pathway peculiarities, wagon group lengths, breaking curve styles, initial wagon group speed and environment conditions, are suggested. The suggested set of factors are characterized from the point of regression analysis. The replacement of some continuous factors with lexical ones are suggested. Decision tree-based classificators are suggested to perform the classification of hump retarder conditions. The decision tree-based classificators can be built with the means of Data Mining on a training set. An improved method of building decision trees is suggested. It’s advantage over the existing algorithms is shown on evaluation sets.

Keywords: hump yard, wagon retarders, regression, decision trees, classification, data mining, multi-factor analysis, soft computations