Improvement of the system for assessing the stability of the railway track section for prospective planning of straightening works

Abstract

Modern requirements for the organization of track maintenance are characterized by two contradictory trends: on the one hand, an increase in freight turnover using high-weight trains and wagons with increased axial load leads to an accumulation of track disorders and an increase in the need for the works; on the other hand, an increase in train traffic density limits the time for preventive and repair work. The existing system of planning straightening works is based on an assessment of the condition of the track based on the results of the passage of track measuring wagons and includes rigidly differentiated terms of work assignment by track classes. Such a system is static and does not allow us to assess the stability of the characteristics of the state of the track in time or during tonnage operation. In modern conditions, when the need for work on a number of sections exceeds the available possibilities in providing additional «windows» in the train schedule, the system of planning the straightening works should be based not on one-time characteristics of the track condition, but on an analysis of the rate of the track degradation during tonnage running up to the maximum level requiring speed limits for train movements. Thus, the order of work assignment should be determined by the rate of deterioration of the track condition in specific sections. This requires the development of a special system for assessing the stability of the track gauge geometry with establishing of the priority order for work on track sections of various lengths. As a solution to this problem, the article proposes a method for a two-component assessment of the stability of the rail track geometry based on the position that the track, as a system, is extensional in length and varying in the course of operation. The proposed system of statistical estimates of the stability of the rail track geometry will allow to identify places that require priority work under conditions of high density of train traffic with limited resources.