Change Detection

Until recently, the railway industry has tended to focus on the measurement of discrete performance parameters in order to determine if a maintenance or safety threshold has been met.

However, this approach is limited to flagging sections of track only once they meet a defined minimum threshold despite the fact that the same section of track may be steadily deteriorating up until that point.

Pavemetrics’ LRAIL turns this process on its end by going beyond discrete measurements to the detection of change in key regions of interest along the track. This method allows track problems to be detected as they develop; well in advance of meeting maintenance or safety thresholds which could result in a closure or speed warning.

The LRAIL’s Artificial Intelligence automatically aligns repeat-runs and then analyzes both 2D and 3D data in order to detect changes between them.

Both positive changes, due to the performance of maintenance, as well as negative can be detected. Example changes that can be detected include:

  • Clip inventory changes including the number of missing or broken clips
  • Spike inventory changes including the number of missing spikes, the number of high spikes, the number of damaged spikes and changes in spike patterns
  • Wooden tie grading and skew angles
  • Concrete tie grading and skew angles
  • Ballast height and fouling level
  • Joint gap and joint bar bolting
  • Changes in gauge, cross level and alignment
  • Changes in rail surface condition

Standard

49 CFR § 213.233 – Track inspections

Related Articles

Laser Triangulation for Track Change and Defect Detection
Authors: Federal Railroad Administration

Laser Triangulation for Track Change and Defect Detection
Authors: Federal Railroad Administration