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Sensors and Intelligent Systems

Recent projects

(1) The Application of Optical Sensors for Railroad Top of Rail (TOR) Friction Modifier Detection and Measurements

The primary objectives of this research are to:

  • Develop technology to detect the condition of top-of-rail lubricity using laser optic reflective sensors and other appropriate optical sensors
  • Assess ToR material content for ToR lubricants, friction modifiers, and flange grease contamination
  • Conduct field tests for new technology for practical application accuracy
  • Develop design capable of movement onboard a Hyrail Vehicle or track geometry car

(2) Monitoring and Detecting Fouled Ballast using Forward Looking Infrared Radiometer (FLIR) Aerial Technology

The primary objectives of this research are to:

  • Use drone-based thermal imaging technology to rapidly and efficiently survey areas of track that may have fouled ballast
  • Provide a historical database for the extent of fouling over time

(3) The Application of Doppler LIDAR Technology for Truck Geometry Assessment

The primary objectives of this research are to:

  • Demonstrate the applicability of LIDAR system for the simultaneous measurement of track speed, distance, track curvature, and track irregularity variations
  • Evaluate the accuracy of the LIDAR sensors in measuring track irregularities as compared with other established rail inspection techniques
  • Study the applicability of the Doppler LIDAR technology for capturing the track-induced dynamics and vibrations
  • Perform comprehensive field tests and collect real-time track geometry data from the Virginia Tech’s LIDAR system and the geometry car equipment for the purpose of performance evaluation and comparison purposes

(4) Ground Trailer Roll Stability Test Evaluation

The project is to perform double-trailer roll stability testing for the evaluation of existing roll stability control (RSC) systems to improve the roll propensity of double-trailers