Automatic Evaluation of Pavement Thickness in GPR Data with Artificial Neural Networks

International science and technology conference "Earth science"

Sukhobok, Y.A.^1 ; Verkhovtsev, L.R.^1 ; Ponomarchuk, Y.V.^1

Far Eastern State Transport University, Department of Computer Engineering and Computer Graphics, 47 Seryshev St., Khabarovsk

680021, Russia^1

关键词: Automatic data processing;    Automatic evaluation;    Automatic selection;    Ground penetrating radar (GPR);    Machine learning techniques;    Multi layer perceptron;    Nondestructive methods;    Pavement thickness;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/272/2/022202/pdf
DOI  :  10.1088/1755-1315/272/2/022202

来源: IOP

【 摘 要 】

The ground penetrating radar (GPR) is one of the most frequently recommended non-destructive methods for the pavement thickness measurement. Due to the rapid growth of GPR data in the recent years, the development of automatic data processing techniques is required. In this paper we propose to use one type of artificial neural network, the multilayer perceptron (MLP), for automatic selection of the pavement boundaries. The experimental results indicate that machine learning techniques can be used for robust road structure evaluation.