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Structural Monitoring and Maintenance
  Volume 2, Number 1, March 2015 , pages 19-34
DOI: https://doi.org/10.12989/smm.2015.2.1.019
 

Delamination and concrete quality assessment of concrete bridge decks using a fully autonomous RABIT platform
Nenad Gucunski, Seong-Hoon Kee, Hung La, Basily Basily and Ali Maher

 
Abstract
    One of the main causes of a limited use of nondestructive evaluation (NDE) technologies in bridge deck assessment is the speed of data collection and analysis. The paper describes development and implementation of the RABIT (Robotics Assisted Bridge Inspection Tool) for data collection using multiple NDE technologies. The system is designed to characterize three most common deterioration types in concrete bridge decks: rebar corrosion, delamination, and concrete degradation. It implements four NDE technologies: electrical resistivity (ER), impact echo (IE), ground-penetrating radar (GPR), and ultrasonic surface waves (USW) method. The technologies are used in a complementary way to enhance the interpretation. In addition, the system utilizes advanced vision to complement traditional visual inspection. Finally, the RABIT collects data at a significantly higher speed than it is done using traditional NDE equipment. The robotic system is complemented by an advanced data interpretation. The associated platform for the enhanced interpretation of condition assessment in concrete bridge decks utilizes data integration, fusion, and deterioration and defect visualization. This paper concentrates on the validation and field implementation of two NDE technologies. The first one is IE used in the delamination detection and characterization, while the second one is the USW method used in the assessment of concrete quality. The validation of performance of the two methods was conducted on a 9 m long and 3.6 m wide fabricated bridge structure with numerous artificial defects embedded in the deck
 
Key Words
    concrete; bridge decks; delamination; modulus; NDT; impact echo; surface wave testing; robotics; automation
 
Address
Nenad Gucunski and Basily Basily: Department of Civil and Environmental Engineering, Rutgers University, Piscataway,
New Jersey 08854, USA
Seong-Hoon Kee: Department of Architectural Engineering, Dong-A University, Busan, 604-714, Korea
Hung La: Computer Science and Engineering, University of Nevada, Reno, NV 89557, USA
Ali Maher: Center for Advanced Infrastructure and Transportation, Rutgers University, USA
 

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