Elastic fastening systems play a crucial part in attaching ties to rail in a way that limits longitudinal and lateral movements of the tie. Missing, loose and damaged clips directly affect the tie’s performance in holding gauge and surface.  However, elastic fastener 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 fastener inspection task by using Artificial Intelligence to analyze both 2D and 3D data in order to more accurately detect elastic fastener type, both present and missing fasteners (and components), loose clips, damaged clips and obstructed 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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