Evaluation And Anlysis Of Track Irregularity Data

In China, the railway safety is always the focus of the railroads’ work, but the condition quality of the railway influences diametrically on driving safety and comfort. The railway track irregularity is not only a measure of the quality of train operation, but also an important point on the safety of train operation. However, the three features--the big data of railway maintenance, fast updating and changing and diverse types, bring the quality assessment of railway track equipment a big challenge. In order to help the staff analysis track irregularity data more precisely, and more quickly find the disease point, we must use scientific analysis method and informatization analysis systems.This paper based on assessment of railway quality by track irregularity data, mainly focuses on researching analysis methods of track irregularity data. Firstly it analyzes and summarizes three different kinds of error by analyzing measuring methods and track irregularity data, and design algorithms to filter out different error:For outlines, a glitch filtered algorithm based on rate of change is proposed in this paper. For intermittent mile error which caused by GPS auto mileage RBI, it is be amended by prolonging mileage along with mile. And for periodic mileage error, it proposed a redressing mileage drift algorithm based on block matching of curvature or superelevation in track irregularity data and curve in the composite chart. Then the method of analyzing and evaluating track state multi-granularity is proposed, which combined with the time domain and frequency domain respectively to analyze track irregularity data. In the time domain, the granularity is divided by mileage, time, channel type and index of evaluation respectively, and the data is analyzed data hierarchically by using the diversification of data. In the frequency domain, by comparative analysis of the existing methods of power spectrum estimation on track irregularity data, the two methods:the welch method and the burg method are proved more suitable for real-time computing spectrum estimation, and the section-balanced spectrum method is proposed. It calculate the lower-higher limit and average value of power spectrum distribution by historical data of each section of line and provide a basis for evaluation of the section’s power spectrum. The results show that the multi-granularity analysis and evaluation method can clearly identify the impact of different particle sizes on the overall results of the evaluation, then to focus on the impact of large particle size analysis and identify the main cause of track irregularity.Finally, the display and analysis system of track irregularity have been designed and built. The system includes two part:track irregularity display and analysis. Display part contains the original waveform view and pre-processing view, analysis part include report graphs and track spectrum in the field of analysis methods and data sources, so various analytical methods and processing algorithms will be realized on this platform, at the same time, it is more convenient to test and debug methods of analyzing track irregularity for the researchers.