Artificial Intelligence for the Condition Assessment of Critical Infrastructure

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The goals of this partnership are to improve testing speed, reproducibility, and accuracy of tools and techniques commonly used for monitoring structural deterioration of concrete. We will use artificial intelligence (AI) and deep learning (DL) to develop automated tools for on-site visual crack inspection and for lab-based microscopic techniques for concrete damage assessment. Our solutions will include rapid and reliable tools to i) automate computation of the cracking index (CI), using a smartphone application ("app") to analyze, in real time, pictures taken in-situ during visual inspections of structures, and ii) to automate the Damage Rating Index (DRI) calculation by applying image analysis (IA) techniques to high-resolution stereomicroscope images of concrete specimens. The proposed technology will significantly enhance two important concrete monitoring techniques: a) computation of the CI, a preliminary assessment of cause and extent of damage based on visual inspection of structures, and b) computation of the DRI, in which core samples retrieved from structures are inspected in a lab-based microscopic protocol to diagnose cause and extent of damage in concrete affected by distress mechanisms such as internal swelling reactions (ISR). Both methods have important limitations: CI requires in-situ qualitative investigations and, although useful as a preliminary indicator, its ability to assess damage of affected concrete is still unclear for structures presenting multiple distress mechanisms and under distinct degrees of confinement and exposure conditions. Computation of the DRI is a time-consuming, expertise-based, lab procedure. Both CI and DRI are subjective in nature and rely heavily on the skill and experience of the person performing the analysis. This project will enable rapid and reliable assessments of the nature and extent of concrete damage in critical infrastructure prevalent in Canada, such as bridges, dams, and buildings. This will, in turn, enable timely and cost-effective preventative rehabilitation strategies, thus ensuring a safer and more reliable built environment.