Title :
Feature Extraction and Selection in Ground Penetrating Radar with Experimental Data Set of Inclusions in Concrete Blocks
Author :
Queiroz, F.A.A. ; Vieira, D.A.G. ; Travassos, X.L. ; Pantoja, M.F.
Author_Institution :
Handcrafted Technol., ENACOM, Belo Horizonte, Brazil
Abstract :
Ground Penetrating Radar systems have been successfully used to access concrete structures conditions. Moreover, inclusions in concrete can be discriminated by simple models based on traces obtained by GPR. In this work, concrete blocks with different inclusions were probed in controlled conditions. Some features were extracted from Ascans of this experimental data set. To get efficient models, raw data were submitted to features selection and space reduction methods. Without complex data pre-processing, good accuracy and more explainable models with less computational burden were obtained.
Keywords :
concrete; feature extraction; ground penetrating radar; radar imaging; A-scans; GPR; complex data preprocessing; concrete blocks inclusions; concrete structures condition access; experimental data set; feature extraction; feature selection; ground penetrating radar; space reduction methods; Concrete; Delay; Machine learning; Concrete; Ground Penetrating Radar; Iterative Search Margin Based Algorithm; Principal Components Analysis; k-Nearest Neighbor;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4673-4651-1
DOI :
10.1109/ICMLA.2012.139