A UAV intelligent anti-collision early warning control method and system when the train loses connection

A technology of train control and control method, which is applied in the field of rail transit, to achieve the effect of preventing continuous tracking due to power exhaustion

Active Publication Date: 2018-10-12
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the current security protection technology, the use of drones is only used as a substitute for manpower most of the time, such as drone line inspection, etc. Most security protection technologies do not address the possible sudden loss of communication. respond to the situation

Method used

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  • A UAV intelligent anti-collision early warning control method and system when the train loses connection
  • A UAV intelligent anti-collision early warning control method and system when the train loses connection

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Embodiment Construction

[0043] The present invention will be further described below with reference to the drawings and embodiments.

[0044] Ordinary railways generally operate at speeds below 180km / h. UAVs in the prior art are used for the UAV early warning device in this scheme. The acceleration time per 100 kilometers of the GTR DRONE produced in Japan is only 1.3s, and It can maintain a cruising speed of 185km / h, and some UAVs in the prior art can reach speeds of more than 200km / h.

[0045] An intelligent anti-collision early warning control method for UAVs when trains lose connection, including the following steps:

[0046] Step 1: Set up workstations at equal intervals along the railway track, and set up several drone early warning devices for each workstation;

[0047] The UAV early warning device communicates with the workstation, and the workstation, the train disconnection early warning center and the ground control center communicate in sequence;

[0048] Step 2: When the train loses contact with ...

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Abstract

The invention discloses a UAV intelligent anti-collision early warning control method and system when a train loses connection. The method improves the UAV and distributes workstations along the railway track to make full use of the flexibility of the UAV. , take the initiative to find and track the lost train, realize the full coverage of the monitoring, and fill the blind area of ​​monitoring the lost train; in addition, the system also uses the UAV early warning device to carry out task handover at the workstation, ensuring the monitoring task. Reliability; at the same time, the train loss early warning center automatically calculates the distance between the lost train and the front train, the lost train and the rear train, and compares it with the front safety distance and the rear safety distance, realizing automatic control The unique alarm trigger mechanism is simple and reliable.

Description

Technical field [0001] The invention belongs to the field of rail transit, and particularly relates to a UAV intelligent anti-collision early warning control method and system when the train is out of connection. Background technique [0002] Rail transit is one of the indispensable forms of transportation in the national comprehensive transportation system. With its low cost, large transportation capacity, little influence by climate and natural conditions, and safety and reliability, it has long been the most important component of the national comprehensive transportation system. Part, it plays a pivotal role in promoting the development of the national economy. [0003] With the increasingly busy rail transit system, in the actual operation and scheduling process, technical errors or sudden changes in the operating environment may cause serious traffic accidents. If the train loses contact with the dispatch center, even if the loss of connection time is very short, there will ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B61L23/00
CPCB61L23/00B64U2101/00
Inventor 刘辉李燕飞李昌泽
Owner CENT SOUTH UNIV
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