Deterioration mapping in subway infrastructure using sensory data of GPR

Abstract

Water infiltration through soil is deemed the most serious problem and the main cause of concrete degradation in subway facilities. A huge amount of water intrusion may accelerate the deterioration mechanisms, such as rebar corrosion, spalling, and water voids. Such mechanisms can compromise the structural integrity and jeopardize public safety. The inspection and assessment of concrete structures are predominantly conducted based on visual inspection technologies. Although, these techniques may be consistent in detecting surface defects, e.g. cracks and spalling, they fall short in identifying subsurface distresses such as air voids, and water voids. Ground Penetrating Radar (GPR) has been extensively utilized for probing concrete infrastructure. Nevertheless, the deterioration mapping of air voids and water voids in concrete has seldom been performed. The objective of this paper is to develop an integrated model based on image processing of GPR profiles to automate air/water voids detection and mapping in subway systems. First, an automated localization scheme is developed to create a consistent inspection pattern. Second, subsurface data are collected in a subway facility, and processed using the image-based analysis technique. Third, the locations and dimensions of the detected defects are mapped to evaluate the severity of deterioration. The developed method is implemented on a tunnel in Montreal subway network. Then, validated via field inspection, digital images, coring samples, infrared thermography and 3D laser techniques. The validation outcomes reflect a strong correlation and compatibility with the generated GPR-based maps. The proposed framework is expected to assist infrastructure managers in identifying critical deficiencies and by focusing constrained funding on most deserving assets.