Analysis and Prediction of Trough Track Superelevation Based on Big Data

The detection of the safety status of urban rail transit is an important part of ensuring the operation of the rail. Using the data detected by the rail to analyze and predict the quality of the rail is very important for the research of rail inspection. Based on the existing research, this paper uses big data to analyze the collected superelevation data, and builds a trough-track superelevation big data prediction model based on the combination of the stochastic oscillation sequence gray model and ALO-Elman network to analyze the historical superelevation data and mine information about superelevation trends. In this paper, the average value of superelevation data of the equal-spaced groove track in a certain interval is collected for verification. The experimental results show that the method can reasonably predict the change trend of the ultra-elevation. The change trend is basically in line with the original data change trend, and the deviation is controlled to be small within range.

HARDWARE AND SOFTWARE FOR MOBILE RAIL INSPECTION TOOLS

The hardware and software used as components for two of the world's most common technologies for continuous ultrasonic nondestructive testing of rails, namely, the classical technology, which consists in pretuning, and the technology of using an adaptive threshold, are considered. As applied to the hardware, the influence of such characteristics as the dynamic range of data recording, as well as the sampling of signal amplitudes is shown. A comparison for both versions of the software is provided. The differences in the interface and functionality are shown. Differences in the algorithms for automated interpretation of ultrasound control data are presented: different approaches to displaying a B-scan (continuous data recording and registration of fragments of flaw patterns with signals that meet the criteria for automated analysis), the possibility and informative value of A-scan, etc. Based on the results of the hardware and software analysis, the capabilities of two of the world's most widely used technologies for non-destructive continuous ultrasonic testing of rails in the world were evaluated.

Responding to the Challenges of Time: Distance Learning in the Field of Non-Destructive Rail Testing

The first experience of remote training of Russian Railways specialists in rail inspection was considered. This modern form of training has proved to be quite effective for improving the qualifications of specialists who already have experience in work. Remote training of beginners is difficult because in a short period of time it is impossible to accommodate a significant amount of necessary knowledge. It is not possible to organize practical classes on setting up and working with flaws and rail samples with various defects. In conclusion, small reviews of the first students are given.