Your browser doesn't support javascript.
loading
Real Depth-Correction in Ground Penetrating RADAR Data Analysis for Bridge Deck Evaluation.
Pashoutani, Sepehr; Zhu, Jinying.
Afiliação
  • Pashoutani S; Department of Civil and Environmental Engineering, University of Nebraska-Lincoln, 1110 S 67th St., Omaha, NE 68182, USA.
  • Zhu J; Department of Civil and Environmental Engineering, University of Nebraska-Lincoln, 1110 S 67th St., Omaha, NE 68182, USA.
Sensors (Basel) ; 23(2)2023 Jan 16.
Article em En | MEDLINE | ID: mdl-36679824
ABSTRACT
When ground penetrating radar (GPR) is used for the non-destructive evaluation of concrete bridge decks, the rebar reflection amplitudes should be corrected for rebar depths to account for the geometric spreading and material attenuation of the electromagnetic wave in concrete. Most current depth-correction methods assume a constant EM wave velocity in the entire bridge deck and correct GPR amplitudes based on the two-way travel time (TWTT) instead of the actual rebar depth. In this paper, we proposed a depth-correction algorithm based on the real rebar depths. To compare different depth-correction methods, we used gprMax software to simulate GPR signals in four models with various dielectric constants and conductivity. The comparison shows that the TWTT-based depth-correction method tends to over-correct GPR amplitudes so that underestimates the deterioration level of concrete decks at certain locations. Two depth-based correction methods are proposed that use migrated amplitudes and further normalize the corrected amplitude by rebar depth (attenuation rate). These methods are then applied to GPR data collected on two bridges, and the results were validated by other NDE methods and chloride concentration test.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Dados Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Dados Idioma: En Ano de publicação: 2023 Tipo de documento: Article