Condition Monitoring of Concrete Structures

由于各种影响，加拿大老化的基础设施显示出恶化和损坏的迹象。2016年加拿大基础设施报告卡(CIRC)的结论是：“在目前的做法(投资、运营、维护)下，大多数基础设施，即使今天处于良好到非常良好的状态，随着它们的老化，将需要越来越大的投资。”在桥梁的具体案例中，中国保监会观察到，桥梁的实际年平均再投资率为0.8%，而资产管理从业者通常将桥梁的再投资率目标定在1.0%至1.7%之间。实际投资的这种不足将不可避免地导致维修项目的优先顺序。对于任何关于结构问题的决策，需要使用先进的传感和计算技术来评估累积损伤的有效方法。如果没有适当的先进工程工具，对基础设施状态的评估可能代价高昂，而且容易出错。结构健康监测已成为保障基础设施安全的重要组成部分。结构健康监测的目标可以概括为：(I)结构性能的成本效益评估，(Ii)损伤的检测和定位，以及(Iii)结构健康预测。结构健康监测的一个重要组成部分是系统识别，其重点是通过响应测量建立有效和可靠的结构模型。结构系统识别需要收集现有结构的数据，如位移、加速度和应变。直到最近，对基础设施最常见的监测是由训练有素的工程师进行目测检查。随着技术的发展，各种其他方法也被引入到结构健康监测领域。以前使用的无损监测技术包括声学、热成像、X射线、图像处理和许多其他需要直接进入结构的所有部分的技术。在复杂结构的情况下，这一条件是不可能实现的。本提案试图集成包括图像处理在内的新技术来研究结构中特定的结构健康管理相关问题。该研究计划的重点是提高在获取基础设施结构完整性方面的SHM应用方面的知识。短期目标是：(I)开发一种评估现有混凝土结构损伤的方法，包括基于计算机视觉的技术；(Ii)建立一种诊断工具，以评估混凝土结构中诱发损伤的范围；以及(Iii)培训高素质的专业人员(HQP)，了解现代技术在SHM中的应用。该研究提案的长期目标旨在为开发一种综合的保健管理工具奠定基础。

Canadian aged infrastructures are showing signs of deterioration and damage due to various effects. The 2016 Canadian Infrastructure Report Card (CIRC) concluded that: "under current practices (investment, operations, maintenance), the majority of the infrastructures, even if in good to very good condition today, will require increasingly larger investments as they age." In the particular case for bridges, the CIRC observed that the actual average annual reinvestment rate of bridges is 0.8%, whereas asset management practitioners typically target a reinvestment rate for bridges in the range of 1.0% to 1.7%. This deficit of the actual investment will lead inevitably to prioritizing maintenance projects. For any decision making concerning structural problems, effective approaches are needed for assessing the accumulated damage using advanced sensing and computational technologies. Without the proper advanced engineering tools, the evaluation of the state of infrastructures can be costly and prone to error. Structural Health Monitoring (SHM) has become a major component to ensure the safety of infrastructures. The goals of SHM can be outlined as: (i) cost effective assessment of structural performance, (ii) detection and localization of damage, and (iii) structural health prognosis. An important component of the SHM is system identification, which focuses on developing an effective and reliable model of the structure through response measurements. Structural system identification requires collecting data from existing structures such as displacement, acceleration and strains. Until very recently, the most common monitoring of infrastructures was carried out using visual examination by trained engineers. With the development of technologies, various other methods have been introduced in the realm of SHM. Nondestructive monitoring techniques used previously included acoustics, thermography, Xrays, images processing and many others which required direct access to all the parts of the structure. This condition is not possible to achieve in case of complex structures. The present proposal attempts to integrate novel technologies including image processing to study specific SHM related problems in structures. The research program focuses on advancing knowledge on SHM applications in accessing the structural integrity of infrastructures. The short term objectives are: (i) to develop a methodology for evaluating damage in existing concrete structures including computer vision-based technology, (ii) to establish a diagnostic tool to evaluate the extension of induced damage in concrete structures, and (iii) to train Highly Qualified Personal (HQP) on the usage of modern technologies in SHM. The long term objective of the research proposal aims at settling the base for developing an integrated tool for SHM.