Clips play a crucial part in the safe and proper functioning of railway fastening systems. Clips are responsible for fastening rails to the underlying base-plate which ensures that rails are securely connected to underlying cross ties (sleepers).

Missing, loose and damaged clips degrade the overall performance of the fastening system and thus their detection is an important railway inspection task. However, clip inspection can be a challenging task for traditional 2D machine vision systems as they come in a wide variety of shapes, sizes and designs thus making them difficult to detect from 2D data alone.

Pavemetrics^® LRAIL™ simplifies the clip inspection task by using Artificial Intelligence to analyze both 2D and 3D data in order to more accurately detect both present and missing clips (and components), clip type, loose clips, damaged clips and covered clips.

Additionally, through the LRAIL’s Change Detection algorithms, changes in clip inventory and conditions can be automatically detected and reported pointing track maintenance crews to the portions of the network that are most in need of attention.

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