2020 Heavy Haul Session
Using Modern Railroad Data Analytics to Minimize Mixed Manifest Train Incident Risk
Instrumented revenue vehicles for heavy-haul track defect monitoring and in-train force validation
RT has extensive experience quantifying the relationship between vehicle dynamics and track geometry via instrumented revenue vehicles and simulation studies.
Extensive research has been conducted that has highlighted that current discrete geometry limits provide a poor correlation with vehicle dynamics and passenger comfort. Several studies conducted by IRT correlating geometry exception reports of discrete defects with instrumented revenue vehicles (IRV) has shown correlations of at best between 30% and 40%. Cyclic and combinational geometry parameters provide an improved correlation with passenger comfort compared with discrete limits as they contain information related to the spatial shape of the defect.
This paper discusses the historical deployment of the technology, but focusses on the recent developments in onboard instrumentation and data analytics to assess and predict degradation of track assets, inform track standards, improve passenger ride comfort and understand in-train forces to aid in the reduction component failures.