Diptojit is currently a PhD candidate in the Experimental Mechanics and NDE Lab at UC San Diego. He obtained his Bachelor's in Civil Engineering from the National Institute of Technology Durgapur, India. He graduated with a Master's in Structural Engineering from the Indian Institute of Technology Guwahati, India. He worked at Larsen and Toubro Construction as a quality control engineer after finishing his bachelor’s degree. Prior to joining UC San Diego, he worked as an assistant professor at Assam Engineering College, India. He was an associate-in (course instructor) at UC San Diego, where he taught solid mechanics. His research interests include non-destructive evaluation (NDE) using ultrasonic waves, acoustic emission, infrared thermography, digital signal processing, and vibration-based structural health monitoring (SHM).
Every year, the railroad industry transports over 10,000 billion freight ton-kilometers and 3000 billion passenger-kilometers around the world. Internal defects in rails and degrading ballast support conditions for railroad ties are some of the major causes of train derailment related accidents. Timely detection of such defects is of critical interest to the railroad maintenance community for ensuring the reliability of the railroad infrastructure. Current inspection techniques for railroad tracks are slow, require specialized test cars in contact with the rails, and can’t be used for continuous monitoring. What if we could enable the trains to perform such inspections during regular service runs? This presentation will delve into the possibility of enabling smart trains, with on-board real-time data acquisition and processing capabilities, for high-speed, non-contact railroad inspections. Results from full-scale field tests with testing speeds of up to 80 mph will be discussed.