关于我们

Product Center

current position: Home > Product Center > Rail transit products
Rear end collision prevention and obstacle detection system

Rear end collision prevention and obstacle detection system

  • Category:Rail transit products
  • Browse number:
  • QR code:
  • Release time:2021-10-22 09:53:05
  • Product description

At present, the advanced automatic train control system is widely used in the subway signal system. ATP protection equipment is installed in all operating trains to protect the train, so as to ensure that the train keeps a distance from the front vehicle and avoid collision. However, how to ensure the safe operation of trains running on the subway line when ATP is abnormal, or there is a faulty train, or there is an engineering vehicle on the line, or there are obstacles on the line track, that is, detect the distance between the front and rear trains, calculate the possibility of collision, detect whether there are obstacles on the track that pose a danger to the train operation, and remind the driver in real time according to the situation, Driver Tian's anti-collision skill is that a PI is in the heart of the 10th day, and a son needs to install our obstacle detection radar on the "ATP outer layer" to form the active anti-collision function of the train.

● functional indexes of millimeter wave anti-collision system:

1. Be able to adapt to trains with maximum running speed of 120km / h and below;

2. Track the end of the train or testing line equipped with anti-collision equipment in the same track in front of the train in real time, and measure its relative distance and speed. The ranging distance shall not be less than 800m, and the real-time ranging error shall not exceed 5%;

3. It has the function of selecting the working conditions of testing line and main line, and has the function of driver confirmation during warning (automatically closing the warning after confirmation);

4. Equipment working status display (self inspection, operation, removal, abnormality or fault), equipment fault information display, working mode display (testing line, main line) and main line distance display;

5. Audible and visual warning, i.e. two-level warning of dangerous distance and emergency braking required by the driver;

6. Overspeed alarm function of testing line (provide overspeed language prompt when judging that the actual speed of the train at the speed limit point is greater than the speed limit value);

7. The system has self diagnosis and log functions, real-time monitoring of key components and recording of fault information and working status. The storage capacity shall not be less than 30 days (first in first out mode is adopted, and the record will overflow automatically);

8. Accident recurrence function, the system can reproduce the scene of historical data;

9. Working voltage: 100VDC, power consumption less than 100W;

10. Reliability index MTBF > 20000h.

● system working principle

Working principle of anti rear end collision and obstacle detection system

The DBF radar is composed of 16 channels of digital radar beam and digital radar antenna, which is composed of 16 channels of radar beam and 16 channels of digital radar antenna.


Rear end collision prevention and obstacle detection system


Working principle of curve diffraction ranging secondary radar

The system consists of coding circuit, modulator, amplifier, isolator, antenna, receiving circuit, signal processing (DSP), interface circuit and control display circuit. As shown in the left box below.


Rear end collision prevention and obstacle detection system


● main technical indexes of obstacle detection radar:

Distance: 0 - 500m;

Angle measurement coverage: ± 10 °;

Ranging accuracy: ≤ 0.3m (radial distance and lateral distance);

Speed measurement accuracy: ≤ 0.5km/h;

Up and down distance: ≥ 500m;

Ranging accuracy: ≤ 3M;

Speed measurement accuracy: ≤ 3.6km/h.

Rear end collision prevention and obstacle detection system

Previous:Rail Transit Sliding Door2021-10-22

Recently Viewed:

Related products

news.related_news