There is a need in the railroad industry to have quantitative information on internal rail flaws, including flaw size and orientation. Such information can lead to knowledge-based decision making on any remedial action, and ultimately increase the safety of train operations by preventing derailments. Current ultrasonic inspection methods leave such sizing determinations to the inspector, and there can be significant variability from one inspector to another depending on experience and other factors. However, this quantitative information can be obtained accurately by 3-D imaging of the rail flaws. It is the goal of this project to develop a portable system that will improve defect classification in rails and ultimately improve public safety.
This paper will present a method for 3-D imaging of internal rail flaws based on Ultrasonic Tomography. The proposed technique combines elements of ultrasonic testing with those of radar and sonar imaging to obtain high-resolution images of the flaws using a stationary array of ultrasonic transducers. The array is operated in a “full matrix capture” scheme that minimizes the number of ultrasonic transmitters, hence simplifying the practical implementation and reducing the inspection time. In this method, a full 3D image of the rail volume identifies the location, size and orientation of the defect. This will help to eliminate human error involved with a typical manual inspection using a single transducer probe inspection. The results of advanced numerical simulations, carried out on a rail profile, will be presented. The simulations show the effectiveness of the technique to image a 5% Head Area Transverse Defect in the railhead. Current efforts are aimed at developing an experimental prototype based on this technology, whose design status is also discussed in this paper.
SIIA: A knowledge based assistant for the SAFT ultrasonic inspection system
