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Comparative Study of Classification Algorithms to Detect Interlayer Debondings within Pavement Structures from Step-Frequency Radar Data | IEEE Conference Publication | IEEE Xplore

Comparative Study of Classification Algorithms to Detect Interlayer Debondings within Pavement Structures from Step-Frequency Radar Data


Abstract:

In the field of civil engineering, Ground Penetrating Radar (GPR) is widely used to monitor structural integrity. With the help of Step-frequency Radar (SFR) for data acq...Show More

Abstract:

In the field of civil engineering, Ground Penetrating Radar (GPR) is widely used to monitor structural integrity. With the help of Step-frequency Radar (SFR) for data acquisition and proper data processing algorithms, it is possible to detect small sub-surface defects within the pavement. In this paper, we discuss a conventional method based on the signal's amplitude, a supervised machine learning method (namely SVM) and a semi-supervised clustering based algorithm to detect said defects. The data are collected using an SFR at IFSTTAR's fatigue carousel where debondings are artificially introduced.
Date of Conference: 22-27 July 2018
Date Added to IEEE Xplore: 04 November 2018
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Conference Location: Valencia, Spain

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