Search

In this paper, the authors examined the change in track gauges in curves for several railway lines with low and high traffic in Hungary (i.e., secondary lines and main lines). They covered the processing of raw data as well as statistical calculations. The considered curved sections were transition curves (TCs) and circular curves (CCs), as well as—in some cases—entire curves (ECs), including TCs and CCs, but not dividing them into parts. The change of track gauge parameter as a function of elapsed time was analyzed based on the distribution functions by calculating the Vaszary-type shape number. A statistical test with the Kolmogorov–Smirnov test was performed, in which the question as to whether the measurement data of the railway lines followed a normal or lognormal distribution was examined; additionally, the skewness and kurtosis parameters were calculated and analyzed. The authors also took into account the impact of the track system and the sleepers. For the selected curves, the authors observed how the average track gauge changes and categorized them according to tolerances. In presenting and summarizing the tests, the authors formulated a conclusion for each study fulfilled. Despite higher traffic loads, the value of track degradation over time is lower for mainline curves than for secondary line curves. It is because the main line has stricter tolerances due to the higher speeds allowed, and more maintenance work is carried out on these lines. The authors concluded that the type of the track system and the sleeper type also influence the change in track gauges in curves. The accurate deterioration ratios for all analyses are contained in the paper. [ABSTRACT FROM AUTHOR]

This paper deals with the time-frequency characteristic analysis for track geometry irregularities using field data recorded by a comprehensive track inspection train. The parameters of the track gauge and the left and right rail alignment are considered to identify their characteristic wavelengths and the locations of their waveforms. In addition to the conventional time and frequency domain analysis, auto-adaptive signal decomposition techniques are used on four pre-selected track sections. During the time series analysis of the track gauge, the cumulative difference from the mean value is calculated, which makes it possible to distinguish the track section constructed with non-standard initial track gauges. The sensitive wavelengths of the track irregularities are obtained from the proper allocation of wavelength ranges in the Fourier Amplitude Spectrum of the original signal and the Fourier transform of the components detected by the Variational Mode Decomposition. This analysis can elucidate the wavelengths and positions of track irregularities that affect vehicle responses. [ABSTRACT FROM AUTHOR]

In this paper, the authors examined the change in track gauges in curves for several railway lines with low and high traffic in Hungary (i.e., secondary lines and main lines). They covered the processing of raw data as well as statistical calculations. The considered curved sections were transition curves (TCs) and circular curves (CCs), as well as—in some cases—entire curves (ECs), including TCs and CCs, but not dividing them into parts. The change of track gauge parameter as a function of elapsed time was analyzed based on the distribution functions by calculating the Vaszary-type shape number. A statistical test with the Kolmogorov–Smirnov test was performed, in which the question as to whether the measurement data of the railway lines followed a normal or lognormal distribution was examined; additionally, the skewness and kurtosis parameters were calculated and analyzed. The authors also took into account the impact of the track system and the sleepers. For the selected curves, the authors observed how the average track gauge changes and categorized them according to tolerances. In presenting and summarizing the tests, the authors formulated a conclusion for each study fulfilled. Despite higher traffic loads, the value of track degradation over time is lower for mainline curves than for secondary line curves. It is because the main line has stricter tolerances due to the higher speeds allowed, and more maintenance work is carried out on these lines. The authors concluded that the type of the track system and the sleeper type also influence the change in track gauges in curves. The accurate deterioration ratios for all analyses are contained in the paper.

This paper deals with the time-frequency characteristic analysis for track geometry irregularities using field data recorded by a comprehensive track inspection train. The parameters of the track gauge and the left and right rail alignment are considered to identify their characteristic wavelengths and the locations of their waveforms. In addition to the conventional time and frequency domain analysis, auto-adaptive signal decomposition techniques are used on four pre-selected track sections. During the time series analysis of the track gauge, the cumulative difference from the mean value is calculated, which makes it possible to distinguish the track section constructed with non-standard initial track gauges. The sensitive wavelengths of the track irregularities are obtained from the proper allocation of wavelength ranges in the Fourier Amplitude Spectrum of the original signal and the Fourier transform of the components detected by the Variational Mode Decomposition. This analysis can elucidate the wavelengths and positions of track irregularities that affect vehicle responses.