Ground-penetrating radar railroad ballast inspection with an unsupervised algorithm to boost the region of interest detection efficiency

Yu Zhang; Anbu  S. Venkatachalam; Tian Xia

doi:10.1117/1.JRS.9.095058

24 July 2015 Ground-penetrating radar railroad ballast inspection with an unsupervised algorithm to boost the region of interest detection efficiency

Yu Zhang, Anbu S. Venkatachalam, Tian Xia

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 095058 (July 2015). https://doi.org/10.1117/1.JRS.9.095058

Abstract

Railroad ballast inspection is critical for the safety of both passenger and freight rail. Ground-penetrating radar (GPR) has been utilized as a highly efficient nondestructive evaluation and structural health monitoring technique in bridge and roadway inspection for many years. However, the development of robust GPR technologies for railroad ballast inspection is still at its early stage due to the complex scattering characteristics of ballast and the lack of efficient algorithms to process big GPR data. An efficient unsupervised method for detecting the region of interest in ballast layer based on the Hilbert transform and Renyi entropy analysis is developed. Both laboratory test and field test are set up and conducted. The data interpretation results demonstrate that the developed region of interest detection algorithm is an efficient and valuable tool for GPR data processing.

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Yu Zhang, Anbu S. Venkatachalam, and Tian Xia "Ground-penetrating radar railroad ballast inspection with an unsupervised algorithm to boost the region of interest detection efficiency," Journal of Applied Remote Sensing 9(1), 095058 (24 July 2015). https://doi.org/10.1117/1.JRS.9.095058

Published: 24 July 2015

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