CPS:Small: A Unified Distributed Spatiotemporal Signal Processing Framework for Structural Health Monitoring

小型：用于结构健康监测的统一分布式时空信号处理框架该奖项是根据2009年美国复苏和再投资法（公法111-5）资助的。本研究的目的是通过开发统一的信号处理框架，将时空传感数据与基于物理和数据驱动的模型相结合，以满足全球对提高重要基础设施安全性和降低维护成本的迫切需求。该方法的结构沿着以下方向：研究动态结构统计建模的可行性，以解决遥感数据的时空相关性；开发高效的分布式损伤检测和定位算法；通过战略性传感器布局研究网络增强；求解递归局部结构状态估计和预测的最优传感器协作。智力优势：与当前结构健康监测领域的最新技术相比，这种创新的统一框架方法具有更可靠、更高效和更好的可扩展性的潜力。拟议的研究也很实用，因为它允许分析真实世界的数据，这些数据考虑了传感器的结构特性、环境噪声和完整性损失。重大损害的概率表示可以提供更多信息的风险评估。更广泛的影响：该项目的结果将为安全性和可靠性迈出重要的一步，尽管会增加动态系统的复杂性。在这个项目中开发的新模型和算法是通用的，可以在涉及分布式递归状态估计、分布式变更检测和数据融合的许多其他领域和应用中做出贡献。该项目将成为教育和培训下一代CPS研究人员和工程师的良好教育平台。该项目将在研究生和本科阶段支持女性学生和美洲原住民学生等代表性不足的群体。

CPS: CPS:Small: A Unified Distributed Spatiotemporal Signal Processing Framework for Structural Health MonitoringThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is to meet the urgent global need for improved safety and reduced maintenance costs of important infrastructures by developing a unified signal processing framework coupling spatiotemporal sensing data with physics-based and data-driven models. The approach is structured along the following thrusts: investigating the feasibility of statistical modeling of dynamic structures to address the spatiotemporal correlation of sensing data; developing efficient distributed damage detection and localization algorithms; investigating network enhancement through strategic sensor placement; addressing optimal sensor collaboration for recursive localized structural state estimation and prediction.Intellectual merit: This innovative unified framework approach has the potential of being more reliable and efficient with better scalability compared to the current state-of-the-art in structural health monitoring. The proposed research is also practical as it allows analysis of real-world data that accounts for structural properties, environmental noise, and loss of integrity over sensors. Probabilistic representation of significant damages allows more informative risk assessment. Broader impacts: The outcome of this project will provide an important step toward safety and reliability albeit increasing complexity in dynamic systems. New models and algorithms developed in this project are generic and can contribute in many other areas and applications that involve distributed recursive state estimation, distributed change detection and data fusion. This project will serve as an excellent educational platform to educate and train the next generation CPS researchers and engineers. Under-represented groups such as female students and Native American students will be supported in this project, at both the graduate and undergraduate levels.