Rail transit safety intelligent monitoring method based on big data analysis and cloud monitoring platform

Abstract

The invention discloses a rail transit safety intelligent monitoring method based on big data analysis and a cloud monitoring platform. The rail transit safety intelligent monitoring method comprises the steps of acquiring a railway track image of each detection sub-region, carrying out the image preprocessing, acquiring the horizontal height of each sleeper in each detection sub-region, the crack length, the contact area of a rail fastener on each sleeper and a steel rail and the distance of each horizontal line of the section of the steel rail, comparing the parameters with corresponding standard data respectively, and then counting and displaying a rail quality safety coefficient and a corresponding quality safety level. The rail transit safety intelligent monitoring method has the advantages of high authenticity and high reliability, the labor cost is greatly reduced, the problem of large detection data error caused by human factors is avoided, the safety and smoothness of railway transportation are ensured, the operation efficiency is improved, and powerful technical support is provided for the safety application of railway tracks.

Description

technical field [0001] The invention belongs to the technical field of rail traffic monitoring, and in particular relates to a rail traffic safety intelligent monitoring method and a cloud monitoring platform based on big data analysis. Background technique [0002] With the rapid development of high-speed railways at any time, the safety of railway operations has become more and more the key to personal safety and economic development. The vibration and impact of trains in long-term operation will inevitably cause safety problems on railway tracks, such as sleepers on sleepers. The track fasteners are loose or more seriously falling off, which seriously affects the safe operation of the train. The sleeper is exposed to the wind and sun in the outdoor environment, and it is easy to be damaged and cracked, and the track is uneven. In order to ensure the safety and smoothness of railway transportation , To improve operational efficiency, real-time monitoring of railway health ...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of high-speed railways at any time, the safety of railway operations has become more and more the key to personal safety and economic development. The vibration and impact of trains in long-term operation will inevitably cause safety problems on railway tracks, such as sleepers on sleepers. The track fasteners are loose or more seriously falling off, which seriously affects the safe operation of the train. The sleeper is exposed to the wind and sun in the outdoor environment, and it is easy to be damaged and cracked, and the track is uneven. In order to ensure the safety and smoothness of railway transportation , to improve operational efficiency, real-time monitoring of railway health status is necessary

[0003] Since the existing railway track inspection method is artificially inspected at a certain time interval, the inspection area cannot be close to the inspection personnel, especially when there are many bridge points to be inspected, it is necessary to equip different inspection personnel for different inspection points. It will bring great inconvenience to the inspectors and increase the cost of inspection. The manual inspection method also has the problem of being unable to achieve real-time inspection. If the inspectors do not perform real-time inspection, then the relevant departments will not be able to know the real-time data of the expansion joints of the bridge. And manual detection will cause errors in the detection data due to human factors, and the accuracy cannot be guaranteed

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