We present a new method of Track Quality Assessment. The method is based on the application of the QCDF as the approach to assessment of the results obtained from periodic track geometry measurements. Results of track geometry measurements comprise a random set of data that can be fully described only by the Irregularity Size Distribution Function (ISDF). Currently, the common approach to track condition analysis and track maintenance planning includes the use of only one of this random process’s parameters, namely, the Standard Deviation (SD).
We have studied the properties of this random process and have evaluated the attainable degree of accuracy when using SD for:
• Track condition analysis;
• Selection of interventional parameter and its threshold value for maintenance planning.
We have concluded that application of SD approach produces inaccurate and non-optimal results. Conversely, use of QSDF produces accurate description of the track condition based on analysis of defects’ physical parameters, and allows to register with high resolution changes (even when SD value doesn’t change) in track condition caused by both regular operation, and use of maintenance equipment.
QCDF is the linear transformation of ISDF and returns the cumulative length of each type of track irregularities with size above threshold value. QCDF is invariant to ISDF distribution law and is monotone, continuous, and its use does not distort ISDF. Use of QCDF allows to identify intervention threshold for track maintenance based on objective assessment of track quality condition. QSDF can be used both as a stand-alone method and as application to SD analysis.

track quality assessment, track geometry, irregularity size distribution function, quasi cumulative distribution function, track maintenance