Hybrid bridge weight in motion (BWIM) and structural health monitoring (SHM) systems

拟议的项目将开发适用于主要公路桥梁的混合桥梁运动称重（BWIM）和结构健康监测（SHM）系统。该系统将提高在各种交通和天气条件下运行的多车道桥梁中部署的BWIM系统和检查程序的效率和准确性。开发的系统有望通过使用概率分析方法而不是确定性解决方案、实时集成传感器阵列、创新传感技术和云基础分析来提高目前使用的BWIM或SHM方法的可靠性和鲁棒性。拟议的bwin - shm系统将通过在新不伦瑞克省的两座主要公路桥梁上设计、开发和实施混合系统来验证。该项目将支持NBDTI开发和验证适用于混合bwin - shm系统的几种先进集成技术的准确性和功能。拟议的系统将为NBDTI和其他运输当局提供一种具有成本效益，非破坏性，永久性和方便的替代方案，以取代当前的运动称重系统，同时为关键桥梁的状态监测提供SHM功能。三名研究学员将在桥梁工程的专业主题上接受高级培训，重点是荷载等级，桥梁结构评估，桥梁动力学和数值模拟。该提案强调了在研究团队和整个培训计划中提高公平性、多样性和包容性的举措。这项研究将有助于跨越多个学科的现有知识体系，包括桥梁工程、数值模拟、系统识别、数字缠绕和物联网。

The proposed project will develop hybrid Bridge Weigh-In- Motion (BWIM) and Structural Health Monitoring (SHM) systems applicable to major highway bridges. This system will improve the efficiency and accuracy of BWIM systems deployed and inspection procedures used in multi-lane bridges that operate under a range of traffic and weather conditions. The developed system is expected to improve the reliability and robustness of currently used BWIM or SHM methods through using probabilistic analysis approaches rather than deterministic solutions, real-time integrated sensor arrays, innovating sensing technologies, and cloud base analytics. The proposed BWIM-SHM system will be validated through the design, development, and implementation of the hybrid system on two major highway bridges in the Province of New Brunswick. This project will support NBDTI in developing and validating the accuracy and functionality of several advanced and integrated technologies applicable to a hybrid BWIM-SHM system. The proposed system would provide NBDTI and other transportation authorities a cost-effective, non-destructive, permanent, and convenient alternative to the current weigh-in-motions systems and simultaneously offer SHM functionalities for condition monitoring of critical bridges. Three research trainees will receive advanced training in specialized topics in bridge engineering focusing on load rating, bridge structural assessment, bridge dynamics, and numerical modelling. This proposal highlights initiatives to improve equity, diversity, and inclusion within the research team and throughout the training plan. This research will contribute to the existing body of knowledge across multiple disciplines including bridge engineering, numerical simulation, system identification, digital twining, and internet of things.