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Abstract:This report documents a multi-year, multi-member collaborative research effort to demonstrate machine-vision enabled wheel/rail characterization, monitoring and analytics. A unique suite of data acquisition equipment was employed. In-track laser wheel scanning, wayside Lateral over Vertical (L/V) force measurement, Truck Bogie Optical Inspection (TBOGI), and Track Geometry Car (TGC) track inspection technology were combined with a Data Collection Consist (DCC) in revenue service equipped with on-board accelerometers, acoustic and propulsion energy recording devices, and a bogie with two instrumented wheel sets. The effort primarily targeted two required FTA Solicitation categories: Operational Safety & System Resiliency. Enhanced operational safety was demonstrated through data collection supporting analytics to proactively assess conditions to enhance system safety. Conditions were monitored by the wheel/rail characterization and analytics systems. Comparisons of “before event” system data signatures with “after event” system data signatures accurately identify track flaws and damage and failure points to accelerate repairs and service recovery following an event.
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