Predictive Monitoring of Rail Infrastructure: A Case Study

Last Updated on 25th April 2022

Maintaining the safe operation of railway networks is paramount for railway authorities. Railway operation safety relies on the conditions of the rail tracks, facilities and infrastructure. 

The UK alone has over 20,000 miles of railway track, more than 2,500 stations and thousands of bridges, signals and viaducts. In the UK, much of the data on rail infrastructure has traditionally been collected manually. This is a time-consuming process that takes valuable resources. Data is then sent to analysts and this whole process is extremely labour-intensive. But the technology to improve this is developing fast, as our case study demonstrates.

Infrastructure Monitoring using Mobile Mapping Systems

Keeping track of all these rail infrastructure elements, especially when a railway network is in operation can be a huge challenge. Track maintenance relies on highly accurate position measurements, and these need to be captured safely and effectively.

This is where LiDAR sensors come in. They add an extra data set that can help to make up for missing or faulty measurements from satellite navigation systems. They can sense infrastructure elements and track geometry, helping to assess the condition of the railway. Integrating LiDAR scans into infrastructure monitoring processes makes them more robust and reliable. They’re also valuable in improving existing train localization approaches.

LiDAR Infrastructure Monitoring: Rail Applications

3D Laser Mapping Ltd, now part of GeoSLAM, specialises in the development of automated 3D monitoring systems and 3D mobile mapping systems. The company’s objective was to design and develop an advanced mobile infrastructure scanning system for geotechnical applications.

Maintaining safe operation of railway networks is paramount for railway authorities. Railway operation safety relies on the conditions of the rail tracks, facilities and infrastructure.  Through the KTP, the company aims to generate a step change in the performance and usability of mobile mapping systems for high accuracy engineering measurements.

The challenge: predictive monitoring

Monitoring the conditions of rail tracks and other rail infrastructure proves to be a challenging task. The aim of the KTP was to design a system that provides a long-term predictive monitoring solution based on accurate, near real-time data on potential dangers and risks to track safety, allowing infrastructure owners to develop a predictive rather than planned approach to maintenance.

Our response: improving LiDAR monitoring systems

The development of automated processing algorithms to improve positional accuracy of mobile LiDAR monitoring systems. These algorithms are critical in enabling the development of the next commercial version of the product. The company now has a much deeper understanding of the algorithms required to automate mobile data processing.

The impact on railway infrastructure

3D Laser Mapping has solid foundations to develop the next generation of mobile monitoring products. The proposed device will be a fully automated, advanced laser scanning system to record geotechnical and surrounding infrastructure conditions in near real time. Placed directly on trains across a whole network, the device will regularly record & monitor conditions on every track, providing high precision data to authorities responsible for maintaining infrastructure.

  • 3D Laser Mapping has had a long standing relationship with the Nottingham Geospatial Institute (NGI), tapping in to its world-leading expertise in GNSS positioning and processing technologies, combined with experience in advanced big data analysis techniques in 3D.
  • PhD graduate, Dr Julia Jing was recruited following the completion of her PhD in Engineering Surveying and Space Geodesy at the NGI.
  • Dr Graham Hunter, Managing Director of 3D Laser Mapping said “The KTP has enabled us to develop core technology to extend the reach of our current product portfolio into new market sectors”.
  • Dr Xiaolin Meng, Associate Professor and Director of the Sino-UK Geospatial Engineering Centre said “Our work with 3D Laser Mapping has directly contributed towards the knowledge of LiDAR (light detection and ranging) applications for a range of projects at the Institute”.

Train Borne Localization System: An Update

With the use of mobile laser scanners, it is possible to recognize infrastructure objects from the trains themselves. Technology and algorithms have developed since this case study was published and rail detection using LiDAR sensors is now even more robust. Asset management for railways is more efficient thanks to the implementation of such systems.