Artificial Intelligence for the Condition Assessment of Critical Infrastructure

这一合作伙伴关系的目标是提高测试速度、重复性和准确性，以及通常用于监测混凝土结构劣化的工具和技术的准确性。我们将使用人工智能(AI)和深度学习(DL)来开发自动化工具，用于现场可视裂缝检查和基于实验室的微观技术，用于混凝土损伤评估。我们的解决方案将包括快速和可靠的工具，用于i)自动计算开裂指数(CI)，使用智能手机应用程序(“APP”)实时分析在结构视觉检查期间拍摄的现场图片；以及ii)通过将图像分析(IA)技术应用于混凝土试件的高分辨率立体显微镜图像，实现损伤等级指数(DRI)计算的自动化。拟议的技术将显著加强两项重要的混凝土监测技术：a)计算CI，基于对结构的目视检查对损坏原因和程度进行初步评估；b)计算DRI，其中从结构中提取的岩心样本在基于实验室的微观方案中进行检查，以诊断受内部膨胀反应(ISR)等损坏机制影响的混凝土损坏的原因和程度。这两种方法都有重要的局限性：CI需要现场定性调查，虽然作为初步指标有用，但对于存在多种损坏机制和不同程度的限制和暴露条件的结构，其评估受影响混凝土损伤的能力仍然不清楚。DRI的计算是一个耗时的、基于专业知识的实验室程序。CI和DRI本质上都是主观的，在很大程度上依赖于执行分析的人员的技能和经验。该项目将能够快速、可靠地评估加拿大流行的关键基础设施(如桥梁、大坝和建筑)中混凝土损坏的性质和程度。这将使及时和具有成本效益的预防性康复战略成为可能，从而确保更安全和更可靠的建筑环境。

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.