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Network Rail took advantage of that opportunity with recent tests of a powerful helicopter-carried camera system, it announced this week (11 March).
The infrastructure owner and manager’s air operations team trialled the system, which combines high-resolution photography with laser surveys and near-infrared images, at its test track near Nottingham.
Installed in a pod beneath a Eurocopter Twin Squirrel helicopter, the Multi-Angle Camera System (Macs) covered “many miles” of railway at the Rail Innovation and Development Centre in Melton in a single shift. The project involved multiple missions along the 13-mile route, giving engineers a detailed view of the track and surrounding environment.
“Passengers and freight customers deserve a reliable railway and the best way to provide that is to know as much about our network as we can, to spot problems before they happen and maintain it to the highest standards,” said Sean Leahy from the air operations team.
“We have brilliant colleagues who are able to work wonders but they can’t be everywhere on the 20,000 miles of track we look after. The Macs is one of the ways we can help them by giving them the best data we can.”
The Macs onboard laser creates a point cloud of up to 300 points per square metre, which can be used to build a 3D model of the railway, including overhead wires, bridges and more. Three 150 megapixel RGB cameras facing forward, sideways and straight down also take images, which are geometrically corrected to make them useful for engineering purposes. A fourth takes near-infrared images, which can be used to determine plant and tree health.
The images are then linked through an inertial measurement unit to provide accurate location data.
The system can also provide digital terrain maps without trees or buildings to help geotechnical engineers see the railway clearly and understand the nature of any potential failures, enabling them to take action.
“We operate one of the busiest railways in the world, with over seven million train movements per year, making traditional ‘boots on ballast inspections’ a real challenge,” said Bradley Sparkes from Network Rail’s technical authority team.
“When we do ultimately decide to send an engineer on site for a closer inspection, we need to be sure we’re basing such a deployment on comprehensive and robust prior intelligence. This will help to drive a reduction in inspection related emissions, improvements in worker safety and enhanced asset intelligence.”
Data from the Macs will provide a solid foundation on which machine learning algorithms for an array of disciplines could be trained. This will help lead the way to use of survey-grade drones, which Network Rail said will be able to fly increasingly long distances as ‘beyond visual line of sight’ capabilities mature.
The Macs will be offered to Network Rail regions as part of the suite of equipment that can be carried by the helicopter.
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