作　　者： ; ;

机构地区： 汕头大学

出　　处： 《土木工程学报》 2010年第3期106-110,共5页

摘　　要： 结构的模态参数识别是结构健康监测系统的基本任务。随着工程结构的日益大型化和复杂化,振动测试时需要布置大量的传感器。传统的集中采集和处理技术将难以胜任海量数据的处理要求,采用无线智能传感器的结构健康监测系统正是应运而生的新方向,而分布式采集和处理是其特点。在无线智能传感网络拓扑结构中采用分布式算法求解结构整体振型,利用随机子空间法识别各子结构模态,结合粒子群优化算法调整子振型获取结构整体振型。通过混凝土钢管拱桥模型试验验证了分布式算法的可行性,并利用模态置信度(MAC)对比分析了由分布式模态识别方法和集中式模态识别方法得到的结果,结果表明两种算法吻合较好。 Identification of the dynamic characteristics of civil structures is important in structural health monitoring. A large number of data must be available from a dense array of sensors for large-scale civil structures and poses a big challenge to the conventional centralized processing technique. Smart sensor networks （SSN） with decentralized processing capability provides new possibilities for structural health monitoring. A distributed method is proposed to calculatc the global mode shape in SSN. Stochastic subspace identification is implemented to identify local mode shapes which are rescaled by using particle swarm optimization method, and subsequently to combine global mode shapes. Using an arch bridge model as an example, the distributed method is shown to be effective. The global mode shapes are close to those from centralized method according to modal assurance criterion （MAC）.

关 键 词： 结构健康监测 智能传感器网络 模态识别 集中式 分布式

领　　域： [建筑科学]