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Communication Dans Un Congrès Année : 2018

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

Résumé

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.

Domaines

Génie civil
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Dates et versions

hal-04287917 , version 1 (15-11-2023)

Identifiants

Citer

Shreedhar Savant Todkar, Cedric Le Bastard, Vincent Baltazart, Amine Ihamouten, Xavier Dérobert. Comparative Study of Classification Algorithms to Detect Interlayer Debondings within Pavement Structures from Step-Frequency Radar Data. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Jul 2018, Valence (Espagne), Spain. pp.6820-6823, ⟨10.1109/IGARSS.2018.8518959⟩. ⟨hal-04287917⟩
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