Railway platform weather dynamic monitoring system based on artificial intelligence

Abstract

The invention provides a railway platform weather dynamic monitoring system based on artificial intelligence. The railway platform weather dynamic monitoring system comprises a carrying device, a freight train platform, a microwave radiometer, a positioning device, a controller, a wireless transmission module and a data processor; the carrying device is hung on a freight train platform, the microwave radiometer is arranged on the carrying device, the positioning device is used for positioning the current position of the freight train platform, the controller is connected with the wireless transmission module, the controller is used for sending positioning information detected by the positioning device and environment information detected by the microwave radiometer to the data processor through the wireless transmission module; and the data processor is used for processing the positioning information and the environment information to obtain atmospheric observation data of a place corresponding to the positioning information. According to the railway platform weather dynamic monitoring system based on the artificial intelligence, meteorological data along a railway line are collected and researched based on a railway system, and real-time data such as ground strong wind, air temperature, rainfall, sand dust and hail are mainly adopted to accurately reflect meteorological condition space-time change characteristics along the railway line.

Description

technical field [0001] The invention relates to the technical field of meteorological dynamic monitoring, in particular to an artificial intelligence-based meteorological dynamic monitoring system for railway platforms. Background technique [0002] With the rapid development of high-speed rail transportation, the volume and speed of high-speed rail transportation have increased rapidly, which puts forward higher requirements for the safety and security of transportation. Meteorological disasters (rain, snow, wind, thunderstorm, low visibility, etc.) and secondary disasters induced by them (such as debris flow, waterlogging, roadbed collapse, etc.) have a great impact on the safe operation of high-speed rail and infrastructure. [0003] At present, the meteorological data along the railway line used in the research is limited, mainly using historical data such as ground wind, temperature, precipitation, dust, hail, etc. There are few meteorological observation data near the ...

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Problems solved by technology

[0003] At present, the meteorological data along the railway line used in the research is limited, mainly using historical data such as ground wind, temperature, precipitation, dust, hail, etc. There are few meteorological observation data near the railway line, and it is difficult to accurately reflect the temporal and spatial variation characteristics of meteorological conditions along the railway line

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