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Proceedings Paper

Railroad track monitoring using ground-penetrating radar: simulation study and field measurements
Author(s): Ram Mohan Narayanan; Chris J. Kumke; Dingqing Li
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Paper Abstract

The subsurface conditions of a railroad track bed have a significant influence on track performance. The depth of the ballast, subballast, and subgrade layers, as well as the presence of water pockets, slurry and other foreign materials all affect track performance. Railroad tie integrity is also an important factor that needs to be monitored for optimum track performance. The possibility of using ground penetrating radar (GPR) to monitor various track parameters in a rapid, synoptic, and non-destructive manner is shown in several simulations presented in this paper. The pulse radar simulations are performed at two different frequencies (100 MHz and 400 MHz). The choice of the two frequencies is dictated by the combined need to perform high resolution probing near the surface (400 MHz), and to probe deeper into the substructure, albeit at lower resolution (100 MHz). The results of the simulation show that the 400 MHz system is better able to estimate the depth of the subsurface layers better than the 100 MHz system. Also, the higher resolution of the 400 MHz system makes it better suited to determine the condition of ties near the surface of the rail bed. However the 100 MHz system is able to better identify anomalies, such as water pockets at deeper depths, compared to the 400 MHz system. Preliminary field experiments at various test tracks also support the above conclusions. It is therefore recommended that a combination of GPR systems at both low and high frequencies be used for optimal monitoring of railroad bed and track condition.

Paper Details

Date Published: 15 October 1999
PDF: 9 pages
Proc. SPIE 3752, Subsurface Sensors and Applications, (15 October 1999); doi: 10.1117/12.365705
Show Author Affiliations
Ram Mohan Narayanan, Univ. of Nebraska/Lincoln (United States)
Chris J. Kumke, Univ. of Nebraska/Lincoln (United States)
Dingqing Li, Transportation Technology Ctr., Inc. (United States)

Published in SPIE Proceedings Vol. 3752:
Subsurface Sensors and Applications
Cam Nguyen, Editor(s)

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