Sensor-Driven Structural Health Prognosis System for Continuous Reliability Assessment of Tubular Steel Structures

本课题的研究目标是开发一种传感器驱动的结构健康预测系统，用于钢管焊接接头疲劳开裂钢结构的可靠性更新和维修调度。将连续传感器数据流与随机退化模型和决策相结合，建立基于概率力学的结构健康预测过程。长期监测系统中传感器的性能退化将在随机方法中得到明确的解释。退化模型将使用贝叶斯和马尔可夫链蒙特卡罗仿真方法进行更新。设计了一种利用柔性压电涂料传感器阵列的疲劳裂纹扩展监测系统。该系统可用于曲面和平面；它将特别为起重机和公路标志支撑结构中常见的焊接管状接头的应用制定和实验验证。交付成果包括基于先进数字信号处理和系统集成方法的传感器驱动结构健康预测和风险分析工具的基本组件和技术设计。该研究结果有望为土木结构的使用状况评估和按需维修延长寿命提供一种有前途的方法。应用实例包括起重机，信号支撑结构和海上结构，以及其他金属结构，如钢桥。研究结果将予以传播，以促进技术转让，使民用基础设施能够巧妙地更新和维护。研究生的教育和专业培训是拟议研究计划的组成部分。将真诚地尝试让合格的代表性不足的学生参与项目研究活动，使他们从拟议的跨学科研究和教育活动中受益。马里兰大学现有的面向高中生和实习工程师的拓展项目将得到充分利用。

The research objective of this project is to develop a sensor-driven structural health prognosis system for reliability updating and maintenance scheduling of steel structures with welded tubular joints susceptible to fatigue-induced cracking. A probabilistic mechanics based structural health prognosis procedure that integrates continuous sensor data stream with stochastic degradation model and decision making will be established. Performance degradation of sensors in long term monitoring systems will be explicitly accounted for in a stochastic approach. The degradation model will be updated using the Bayesian and Markov Chain Monte Carlo simulation methods. A fatigue crack growth monitoring system utilizing the flexible piezoelectric paint sensor arrays will designed. The system can be used on curved and flat surfaces; it will be especially formulated and experimentally validated for applications on welded tubular joints commonly found in cranes and highway sign support structures. Deliverables include the design of fundamental components and technologies for sensor-driven structural health prognosis and risk analysis tools utilizing advanced digital signal processing and system integration methods.The results of this research are expected to provide a promising method to assess the service condition and for extending the life of civil structures through on-demand maintenance. Example applications include cranes, signal support structures and offshore structures, as well as other metal structures such as steel bridges. The results will be disseminated to facilitate the technology transfer that will enable smart renewal and maintenance of civil infrastructures. Education and professional training of graduate students are integral components of the proposed research program. Sincere attempts will be made to involve qualified underrepresented students in the project research activities to benefit them from the proposed interdisciplinary research and education activities. Existing outreach programs for high school students and practicing engineers at the University of Maryland will be leveraged.