Fuxing high-cold intelligent multiple unit is put into operation, with artificial intelligence escort

The development of China’s high-speed railway has changed China’s transportation pattern and has also profoundly affected various fields such as economy, politics and culture. China’s high-speed railway has gradually formed a network from scratch, from point to line, and from line to line. As a “infrastructure maniac”, the high-speed rail route runs through the whole country, and is densely distributed in the north and south. With the help of technology, it also gnaws down the hard bone of “extreme cold weather”.
Since the beginning of winter, Northeast China has experienced many cold wave weather, with the lowest temperature of about minus 50 degrees Celsius. In this extremely cold environment, a high-speed train is still galloping at full speed. Among them, the high-cold intelligent EMU Fuxing in the northernmost alpine region of China, which has just been put into operation, has passed the test of extreme cold relying on a number of “antifreeze” technologies.
When operating in extremely cold areas, it will encounter the problem of snow accumulation at the bottom of the vehicle, the problem of antifreezing and cracking of the body structure at low temperature, the problem of antifreezing and blocking of the circulation system, and the problem of idling and sliding of the train under low temperature conditions, which will ultimately affect the operation safety.
In response to these problems, China Railway Harbin Bureau Group Co., Ltd., relying on advanced technology, has formed a set of operational safety measures to cope with severe cold, ice and snow weather. With the support of artificial intelligence technology, the team developed a set of intelligent image recognition technology, which can automatically identify the snow and ice conditions of the bogie. After the operation of the EMU is completed and put into storage, the key parts can be sprayed with low-pressure warm water to quickly peel off and melt the snow and ice on the bogie.
In terms of efficiency, it used to take 16 people and 4 hours to complete the ice-melting and snow removal of a group of multiple unit trains. It only took 2 people to operate for 1 hour, which reduced the time of multiple unit de-icing operation and effectively accelerated the train turnover efficiency.
In addition to “optimizing” the car body, artificial intelligence technology can also improve the operation line: it is reported that the natural disaster and foreign matter monitoring system set along the high-speed railway, together with various sensors, can identify the wind speed, snow thickness, etc., and “guide” the train to switch to different “speeds” for different wind and snow conditions.
In addition to applications in extreme weather, AI also plays an increasingly important role in daily maintenance. Generally, when riding on the high-speed railway, we often see electrical equipment with numerous pillars and spider nets. Its professional name is catenary. They deliver “electric fuel” to the EMU. The faster the EMU runs, the higher the requirement for the “health” status of the catenary.
In order to reduce potential safety hazards and improve the operation level, AI robots are introduced into the high-speed railway line to provide accurate contact network image data and deal with potential safety hazards. This intelligent analysis system has passed the data test, feedback and correction of more than 30 high-speed railways, more than 40000 kilometers, and more than 1.1 billion parts, forming a large database of catenary equipment defects. The automatic analysis capability covers 2160 types of defects and 514 types of parts of various types of high-speed railways, and the analysis efficiency reaches 200 km/day.
With the help of the 4C catenary inspection vehicle, the main parts, structures and key positions of the catenary equipment are subject to omni-directional and high-precision imaging and acquisition, and then the image data is handed to the “AI robot”, so that the equipment defects can be automatically identified and summarized from the massive image data, which can improve the number and speed of defect detection, and also liberate the analysts from the image screening work to focus on the defect distribution law, defect cause investigation Defect rectification and tracking.
At present, the 4C catenary inspection vehicle on the Beijing-Shanghai high-speed railway can collect up to 3 million equipment images every quarter. Taking 8000 images per person per day as an example, it takes 20 days for more than 20 people to work overtime. With the support of “AI robot”, it only takes two analysts 10 days to complete the analysis of the same 3 million images, and the efficiency is increased by 20 times.