A Japanese railway operator has developed a new inspection train, Big Eye, featuring headlights that resemble a pair of eyeballs, aiming to streamline its maintenance work with digitalized functions.
Kyushu Railway Co. will hold test runs from this month through next March in southwestern Japan before its full-fledged debut to evaluate the equipment’s durability, accuracy of data measurement and for building a system for data analysis, it said.
While the conventional maintenance relies largely on visual inspection, the Big Eye is equipped with laser sensors and cameras to detect track distortions while utilizing big data collected by devices, JR Kyushu said.
The new train can be operated more efficiently, as it is capable of self-driving without a locomotive to pull it, it said, unlike the current active inspection train that has been in use since before 1987 when the state-owned Japanese National Railways was privatized.
“We enhanced the functions (of the train) to allow preventive maintenance of (railway tracks). It is one example of digitalization of railways,” Kyushu Railway President Yoji Furumiya told a press conference in late October.
The red-colored train was remodeled from one that was affected by flooding during torrential rains in July 2020 in Hitoyoshi, Kumamoto Prefecture, in southwestern Japan.
The train also features a cow illustration on the rear side, a nod to Kumamoto, renowned for its beef, and wave patterns on the sides that resemble the track trajectory.
JR Kyushu said it hopes the design will become well known to many people, including children, given the popularity of shinkansen track-testing trains known as Doctor Yellow in Japan.
Using sensors, the Big Eye can collect data on the trajectory of railway tracks and measure the distance between the tracks and infrastructure, including utility poles, tunnels, station platforms and traffic lights.
Continuous shooting by cameras on the train car can be used to check the status of metal fittings that hold the track together.
The collected data are sent to a company system to be analyzed remotely, contributing to reducing the staff needed on the scene. Artificial intelligence technology would be used to analyze images taken by the camera and automatically detect areas needing maintenance, JR Kyushu said.