Using AI to reduce Red Zone Working
New Technologies | Australia | Track Patrol Replacement
The Requirements
To assess the technical capability of the Cordel platform to assist with reducing the number of manual track patrols both on foot and mechanised.
The Red Zone Reduction Program is part of Sydney Trains Intelligent Maintenance Transformation Program (IMTP) and its primary objective is to utilise governance and strategic planning and innovative technology initiatives to reduce staff exposure inside rail corridors.
The Solution
The Cordel platform was deployed on a 40km section of track south of Sydney. They Cordel remote sensing system was temporarily installed on the front of a diesel service locomotive, powered independently which required no additional engineering certifications to install.
The Cordel platform processed the information using deep learning neural networks and the outputs were presented in Cordel Cloud for inspectors to review.
The Results
The Cordel remote sensing hardware was mounted on the front of a service diesel. A 40km section of track was captured, and the Cordel defect detection machine learning algorithms were applied to the resulting data to detect and classify objects, assets and defects. The program successfully demonstrated, using hi-resolution imagery mounted on the front of trains with GPS, it was accurately able to automatically identify, classify and report on the selected defects and asset classes within predetermined accuracies. Defect classes included:
track
sleepers
clips
switches
gantry
ballast
graffiti
signals and
debris
"Results from trials have been encouraging and we are continuing to embed this new capability as the preferred method of inspections for transit space monitoring across the entire ARTC Interstate Network."
Damon Goulding, Asset Planning Engineer
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