Anti-freezing preheating monitoring method and system for D-series High-Speed train

Abstract

The invention relates to an anti-freezing preheating monitoring method for a D-series High-Speed train. The method comprises the steps that (1), a remote temperature acquisition device acquires the temperature of a D-series High-Speed train and transmits the acquired temperature of the D-series High-Speed train to a data center cloud server in real time; (2), after receiving the temperature and attribute information of the D-series High-Speed train, the data center cloud server compares the temperature of the D-series High-Speed train with a set threshold value, and if the temperature of the D-series High-Speed train is greater than the threshold value, the data center cloud server records the position information of the remote temperature acquisition device, the number of the D-series High-Speed train to which the data center cloud server belongs, the temperature of the D-series High-Speed train and transmission time; if the temperature of the D-series High-Speed train is smaller thanthe threshold value, the data center cloud server sends early warning information to a cloud terminal and records the position information of the remote temperature acquisition device, the number ofthe D-series High-Speed train to which the remote temperature acquisition device belongs, the D-series High-Speed train temperature and the transmission time; and (3), the data center cloud server transmits power to the D-series High-Speed train through the cloud terminal for preheating and freezing prevention. The method is used for realizing automatic acquisition, transmission and storage of thetemperature of the D-series High-Speed train and real-time monitoring of the webpage terminal.

Description

technical field [0001] The invention relates to a monitoring method, in particular, to provide an anti-freezing and preheating monitoring method and a system for the anti-freezing and pre-heating of an EMU after stopping. Background technique [0002] With the rapid development of high-speed railway, EMU trains play an increasingly important role in railway passenger transportation. High-speed EMUs bring convenience to people's travel and greatly shorten the travel time, so the safe operation of EMUs appear particularly important. In order to ensure the safe operation and parking of the EMU in winter, during the anti-freezing period every year (November 15-March 15), the EMU needs to be antifreeze and preheated (that is, the EMU should be lifted and powered, and the heating equipment should be operated. increase the interior temperature). At present, most of the anti-freezing and preheating work of EMUs adopts the artificial spot temperature mode, which not only has poor r...

AI Technical Summary

Problems solved by technology

In the process of temperature data collection and transmission, it is necessary to manually measure the ambient temperature and the temperature inside the EMU. The time interval is 1 hour, which cannot eliminate the risk of freezing trains caused by sudden temperature drops.

[0006] (2) Human resources are occupied more

In the traditional working mode, not only the personnel in the maintenance depot and the storage yard are required to monitor the ambient temperature, but also the antifreeze and warm-up personnel are required to monitor the temperature inside each EMU, which takes up a lot of human resources

[0007] (3) The cost of industrial point thermometers is relatively high

The spot thermometer used by antifreeze and preheating personnel to collect the temperature inside the car is an industrial-grade infrared thermometer, which is expensive

[0008] (4) Scheduling work is difficult

EMU temperature monitoring, warm-up job dispatching and many other things increase the difficulty of dispatching control. Whether the anti-freezing and pre-heating can run smoothly requires high quality dispatchers, and there are problems such as untimely response, poor information transmission, and low degree of automation.

[0009] (5) Insufficient application of big data analysis

At present, the historical temperature data collection interval of EMUs is long, and the guiding significance for the temperature change of EMUs within a specific time period is not strong, so it is impossible to realize the prediction of the antifreeze and preheating state of EMUs in winter

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