Prediction model with optimal matching parameters for a dynamic track stabiliser during railway maintenance

Abstract

Nowadays, high-speed and heavy duty trains make ballasted track extremely busy, and thus it is necessary to solve the conflict between the traffic density and the maintenance work load. However, since the mechanical properties of discrete ballast bed are complex, there is a lack of in-depth investigation into the working performance of large-scale railroad maintenance machinery. In this paper, we take the WD-320 dynamic track stabiliser as the research object, to study the effect of operation parameters on the quality state of the ballast bed. Based on the field test data, a prediction model for optimal matching of operation parameters has been constructed, which can be used to estimate, compare and determine the optimal operation parameter combination for the operation process. By operating according to the optimal operation parameter combination, the optimum quality state of the ballast bed can be quickly reached, to solve the conflict between the traffic density and the necessary maintenance window.