Spikes play a crucial part in the safe and proper functioning of railway fastening systems as they are used to secure rails and base-plates to cross ties (sleepers). Spikes come in a variety of shapes and types with some of the most common being cut spikes, dog spikes and chair screws.

Missing, broken and high spikes degrade the overall performance of the fastening system and thus their detection is an important railway inspection task.

However, spike inspection can be a challenging task for traditional 2D machine vision systems due to their lack of 3D data. 3D data is needed to detect high spikes and often to correctly identify spike heads which are difficult to separate from ballast particles due to their similar size and shape in 2D images.

Pavemetrics^® LRAIL™ simplifies the spike inspection task by using Artificial Intelligence to analyze both 2D and 3D data in order to more accurately detect present and missing spikes, spiking pattern, high spikes and broken spikes.

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

Standard

49 CFR § 213.233 – Track inspections

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