Automated 3DGPR Analysis for Concrete Pavement Evaluation

The objective of this project is to identify missing, misplaced, or misaligned dowel and tie bars, voids under joints, and other deficiencies in concrete pavement by automating and improving upon the accuracy and repeatability of the analysis of 3DGPR data. The scope will include collection of 3DGPR data on concrete pavement sections at various field sites and on laboratory test slabs, and using the collected data to develop analysis routines that can be used by Department of Transportation (DOT) personnel to evaluate the conditions of interest. 3DGPR is a relatively new technology for subsurface condition evaluation. It has been implemented by state DOTs through the SHRP2 R06D IAP program and more recently as part of TPF-5(385) and is currently the primary technology being considered in TPF-5(504) led by State. 3DGPR differs from conventional Ground Penetrating Radar (GPR) in that it provides detailed information across the width of a lane, enabling it to detect tie bars, dowel bars, and other spatial features that might be missed by conventional GPR systems. Qualitative review of 3DGPR data can reveal important features in small sections of pavement, but qualitative review requires special expertise and is not practical for larger pavement sections. The purpose of this project is to automate the analysis of the 3DGPR data in a way that produces the relevant useful information needed by the owner agency for making decisions. This collaborative project combines the expertise of Contractor in 3DGPR data acquisition and processing with the expertise of the Marquette University in GPR automated data analysis and machine learning.