Machine Vision System Automation for the Inspection of Moving Trains Using Various Train Detection Sensors

The use of machine vision techniques for the inspection of train components is a new and fast growing research area. Intermodal trains are usually the fastest freight trains in North America. However, since the aerodynamic characteristics of these trains are not the best, fuel consumption tends to be high. If the loads on these railcars were placed in better configurations, it would be possible to optimize fuel consumption, thereby saving fuel costs. To help improve the aerodynamic characteristics of trains, our research group has developed a wayside machine vision system that captures videos of trains passing by. The system consists of various train detection sensors, a camera, rack mount computers, and a lighting tower. After the data is collected, it is analyzed and the train is given an aerodynamic score. My role in this project has been to automate the machine vision system using the signals from the detectors to decide when to execute certain tasks (i.e. adjusting the aperture, starting video recording, etc.) based on where the train is located with respect to the camera. This thesis explains my approach in achieving my goal.Burlington Northern Santa Fe (BNSF)unpublishednot peer reviewedU of I OnlyUndergraduate senior thesis not recommended for open acces