Hierarchical Redundancy-Based Monitoring and Robust Seismic Control Systems

基于分层冗余的监测和鲁棒地震控制系统

• 批准号: 9909247
• 负责人: Adriene Jefferson
• 金额: --
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-03-15 至 2004-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9909247&HistoricalAwards=false
• 关键词: Hierarchical; Redundancy; Based; Monitoring; Robust

9909247YangA redundancy-based monitoring system for civil structures such as bridges, towers, chimneys, dams and buildings with uncertain dynamic properties located in regions that are susceptible to nature disasters is investigated. This Hierarchial Intelligent Monitoring System is projected as an integrated entity consisting of three principal software components which interact seamlessly with each other in real time and are interfaced with the physical structure. These components have data processing and decision-making capabilities organized into a hierarchy of shielded layers, with each layer employing a decentralized topology of information processing units. The shielding of the layers provides data abstraction and the decentralized topology in each layer creates a mechanism of redundancy. In turn, these factors improve the overall performance and reliability of the monitoring system. The elements of the monitoring system are referred to as the Multilayer Expert Module (MEM), the Multilayer Identification Module (MIM), and the Multilayer Control Module (MCM).The Multilayer Expert Module assists in structural health monitoring (both in 'normal' time and also during earthquakes) and employs advanced damage detection and assessment using neuro-fuzzy logic techniques. The Multilayer Identification Module is primarily responsible for maintaining an active database of system models, which are updated appropriately. The control signals developed in the Multilayer Control Module are implemented by the control system hardware on the actual structure, using devices such as active tendons, active variable stiffness systems, active mass dampers, active base isolators, etc., or combinations of these. Model selection in the MIM and control algorithm selection in the MCM are achieved via fuzzy logic based decision support.The main objectives of this project are to develop a sophisticated expert system which can monitor structural health, and which can detect and accommodate failures needing corrective action despite inaccurate sensory data and to build a reliable identification system which interfaces with the physical structure and which can synthesize accurate structural models in real time, despite the presence of structural uncertainties.The investigation addresses several key aspects of structural monitoring practice and will contribute to the development of safer and more reliable infrastructures.

针对自然灾害多发地区的桥梁、塔楼、烟囱、大坝等动力特性不确定的土木结构，研究了基于冗余度的监测系统。 该层次化智能监控系统是由三个主要的软件组件组成的集成实体，这些组件在真实的时间内相互无缝地交互，并与物理结构接口。 这些组件具有数据处理和决策能力，组织成屏蔽层的层次结构，每一层都采用分散的信息处理单元拓扑结构。 层的屏蔽提供了数据抽象，并且每层中的分散拓扑创建了冗余机制。 反过来，这些因素提高了监控系统的整体性能和可靠性。 监测系统的组成部分被称为多层专家模块（MEM）、多层识别模块（MIM）和多层控制模块（MCM）。多层专家模块协助进行结构健康监测（在“正常”时间和地震期间），并采用先进的损伤检测和评估，使用神经模糊逻辑技术。 多层识别模块主要负责维护系统模型的活动数据库，并适当更新。 在多层控制模块中开发的控制信号通过实际结构上的控制系统硬件来实现，使用诸如主动筋、主动变刚度系统、主动质量阻尼器、主动基础隔震器等设备，或这些的组合。 MIM中的模型选择和MCM中的控制算法选择通过基于模糊逻辑的决策支持来实现。本项目的主要目标是开发一个先进的专家系统，可以监测结构健康，并且其能够检测和适应需要校正动作的故障，尽管传感器数据不准确，并且构建与物理结构接口并且能够综合准确的尽管存在结构的不确定性，结构模型在真实的时间。调查解决了结构监测实践的几个关键方面，将有助于更安全和更可靠的基础设施的发展。