TPF-5(504) - Automated Detection of Pavement Subsurface Defects using Advanced NDT/NDE Technologies
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Participating States
FHWA, FL, GADOT, IL, KY, MN (lead state), MO, MS, TN, TX and ND
Contacts
Eyoab Zegeye, Ph.D., P.E., MnDOT, eyoab.zegeye@state.mn.us, Phone: 651-366-5517
Shongtao Dai, Ph.D., MnDOT, shongtao.dai@state.mn.us
Big Picture
MnDOT's mission is to create a safe, accessible, efficient, and reliable multimodal transportation system that connects people to destinations and markets at the state, regional, and global levels. To support this mission, MnDOT is exploring and gradually adopting innovative technologies, including advanced non-destructive testing (NDT) and evaluation (NDE) tools such as 3D Ground Penetrating Radar (3D-GPR) and the Traffic Speed Deflectometer (TSD).
These NDT/NDE technologies enable full-coverage, continuous pavement scoping and evaluation. They allow MnDOT to efficiently determine the thickness of pavement layers, detect and map subsurface defects that are otherwise undetectable through visual inspections or traditional pavement forensic tools, and monitor the structural health of pavement systems.
By leveraging data from these advanced technologies, MnDOT can refine its pavement scoping practices, reduce or eliminate the need for coring (improving both safety and cost efficiency), and identify more effective treatment and rehabilitation strategies. These advancements enhance pavement performance and durability, optimize return on investment, and ensure equitable access to safe and efficient transportation systems.
Purpose of Study
Already, 3D-GPR provides continuous, lane-width imaging of subsurface conditions, enabling the determination of layer thickness and the identification of optimal coring locations for further investigation. This study aims to enhance the automation and reliability of 3D-GPR in detecting, locating, and quantifying the severity of subsurface defects and anomalies, including stripping and other moisture-related damage.
The research will primarily focus on flexible and semi-rigid pavements. If successful, the procedures and algorithms developed in this study will significantly improve the GPR processing experience, drastically reduce the time required for data analysis, and minimize subjectivity. This will ensure consistent interpretations, regardless of the operator’s skill level.
To achieve its objectives, the study is collaborating with member agency engineers, manufacturers, consultants, and researchers. Additionally, it will leverage 12 test sections recently constructed at MnROAD specifically to support this research. These sections include multiple locations with intentionally created and embedded subsurface defects.
The study aims to utilize these test sections for training, calibrating, and validating algorithms designed for the automated detection and quantification of subsurface defects. This investigation will incorporate both advanced and traditional NDT/NDE techniques, including 3D-GPR, TSD, FWD, and IE/SASW, to verify, validate, and complement the outcomes generated by GPR.
Email List
To be added to the project email list, contact Eyoab Zegeye or Katies Johnson:
For more details refer to the official pool fund study pool fund study