International consulting group COWI has won a contract worth approximately £500,000 to combine machine learning and novel subsurface defect detection with existing virtual inspection tools used for bridges so as to reduce the time spent by personnel on the ground examining tunnel structures.
Working with subcontractors Railview and Viapontica over the next 18 months, COWI’s project team will build on mobile mapping solutions using a combination of technologies to collect data that will be processed to build an accurate three-dimensional model, which can be viewed and manipulated by engineers.
The project will be funded by Network Rail through the SBRI: innovation in automated tunnel examination competition, delivered by InnovateUK. The project seeks to improve the accuracy, efficiency and safety of tunnel examinations, resulting in safer and more reliable railway operation.
The new techniques will reduce exposure to health and safety risks and reduce costs while enhancing the asset knowledge of rail staff. The improvements will also lead to less disruption of rail passengers by reducing disruptive possessions required for examinations and allowing timely maintenance interventions.
Andy Sloan, managing director and senior vice president of COWI in the UK, said: “While railway workforce injuries are declining, there is still room for improvement.
“The impact that digital technologies can have on health and safety cannot be understated and this project is a fantastic opportunity for us to bring best practice from across sectors and geographies to further digitalise and improve tunnel inspection.”
The final stage of the project next year will be to undertake an operational environment demonstration and evaluate the results in conjunction with Network Rail’s asset managers. Following that, COWI will submit a report at the end of 2021 and develop plans for further enhancement and exploitation.