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Article
Improved Ground Penetrating Radar Data Processing Method for Railroad Ballast Inspection
Proceedings of the 9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice (2019, St. Louis, MO)
  • Jenny Liu, Missouri University of Science and Technology
  • Hanli Wu
Abstract

Ground penetrating radar (GPR) is a useful tool for railroad track inspection. The use of GPR in the analysis of railroad track condition is desirable since it provides a cost-effective method to examine ballast conditions without digging. However, there is a big challenge for the application of GPR to the railway ballast layers because the relatively large regions of void space in the layer would cause radar signal scattering and make the detection results unreliable. In this study, an improved GPR data processing method for railroad ballast inspection was proposed. A basic set of digital filters was designed to clean up the scan data generated by the radar, and a primary graphical user interface (GUI) was developed for GPR technology to assess the railroad ballast conditions. The lab tests were performed to evaluate the GUI and algorithms proposed in this research. The results indicated that the data processing method was sufficient to detect the ballast layer.

Meeting Name
9th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII-9 (2019: Aug. 4-7, St. Louis, MO)
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
  • Data processing,
  • Ground penetrating radar,
  • Railroad ballast inspection,
  • Short-Time Fourier transform
International Standard Book Number (ISBN)
978-000000000-2
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Publication Date
8-7-2019
Publication Date
07 Aug 2019
Citation Information
Jenny Liu and Hanli Wu. "Improved Ground Penetrating Radar Data Processing Method for Railroad Ballast Inspection" Proceedings of the 9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice (2019, St. Louis, MO) Vol. 2 (2019) p. 1236 - 1241
Available at: http://works.bepress.com/jenny-juanyu-liu/39/