TY - GEN
T1 - Real-time asphalt concrete pavement compaction monitoring using ground penetrating radar
AU - Wang, Siqi
AU - Al-Qadi, Imad L.
AU - Zhao, Shan
AU - Cao, Qingqing
N1 - Publisher Copyright:
© 2019 American Society of Civil Engineers.
PY - 2019
Y1 - 2019
N2 - Real-time density monitoring during pavement compaction process is crucial to ensure asphalt concrete (AC) construction quality. Ground penetrating radar (GPR) may be used for continuous real-time AC density estimation using AC and its components dielectric constants. However, the effect of surface moisture, resulted from roller water sprays, jeopardizes the predicted AC density accuracy. While algorithms were developed to remove the surface moisture effect, they are only applicable to 2 GHz GPR antenna. This study proposed a novel algorithm to remove surface moisture effect based on "frequency-select effect." This algorithm is applicable to most of the GPR antenna central frequencies. The Al-Qadi, Lahouar, Leng (ALL) density prediction model was used in this study. Static field tests were performed using both 2 GHz and 1 GHz air-coupled antenna at the Illinois Center for Transportation (ICT) of UIUC. The GPR signals were processed through proposed algorithm using power spectrum of the surface reflections. There is a high correlation between AC dielectric constant and density; hence, the dielectric constant ground-truth values were used to estimate the errors using the proposed algorithm. The proposed algorithm was found to be efficient and accurate; errors of dielectric constant are less than 3% for the 2 GHz case and 5% for the 1 GHz case, respectively.
AB - Real-time density monitoring during pavement compaction process is crucial to ensure asphalt concrete (AC) construction quality. Ground penetrating radar (GPR) may be used for continuous real-time AC density estimation using AC and its components dielectric constants. However, the effect of surface moisture, resulted from roller water sprays, jeopardizes the predicted AC density accuracy. While algorithms were developed to remove the surface moisture effect, they are only applicable to 2 GHz GPR antenna. This study proposed a novel algorithm to remove surface moisture effect based on "frequency-select effect." This algorithm is applicable to most of the GPR antenna central frequencies. The Al-Qadi, Lahouar, Leng (ALL) density prediction model was used in this study. Static field tests were performed using both 2 GHz and 1 GHz air-coupled antenna at the Illinois Center for Transportation (ICT) of UIUC. The GPR signals were processed through proposed algorithm using power spectrum of the surface reflections. There is a high correlation between AC dielectric constant and density; hence, the dielectric constant ground-truth values were used to estimate the errors using the proposed algorithm. The proposed algorithm was found to be efficient and accurate; errors of dielectric constant are less than 3% for the 2 GHz case and 5% for the 1 GHz case, respectively.
KW - Asphalt concrete pavement compaction
KW - Ground penetrating radar
KW - Real-time density monitoring
KW - Surface moisture
UR - http://www.scopus.com/inward/record.url?scp=85073891482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073891482&partnerID=8YFLogxK
U2 - 10.1061/9780784482476.012
DO - 10.1061/9780784482476.012
M3 - Conference contribution
AN - SCOPUS:85073891482
T3 - Airfield and Highway Pavements 2019: Innovation and Sustainability in Highway and Airfield Pavement Technology - Selected Papers from the International Airfield and Highway Pavements Conference 2019
SP - 106
EP - 111
BT - Airfield and Highway Pavements 2019
A2 - Al-Qadi, Imad L.
A2 - Ozer, Hasan
A2 - Loizos, Andreas
A2 - Murrell, Scott
PB - American Society of Civil Engineers
T2 - International Airfield and Highway Pavements Conference 2019: Innovation and Sustainability in Highway and Airfield Pavement Technology
Y2 - 21 July 2019 through 24 July 2019
ER -