中文摘要：

利用美国伊利诺伊大学结构健康监测项目组研制的ISM400无线智能传感器,分别采用分布式和集中式数据采集方法,对一个简支层压板进行了振动测试试验.采用自然环境激励技术（NExT）和特征系统实现算法（ERA）相结合的一种时域联合算法,仅利用输出信号对结构模态参数进行识别,并将识别结果与有限元模型的计算结果进行了对比分析.根据分布式与集中式两种数据采集处理方法识别的振动频率和模态振型,与有限元数值模拟结果吻合较好,验证了基于分布式数据采集的无线智能传感器网络在结构模态识别中的可行性.在大型土木工程结构需要布置大量传感器时,分布式无线智能传感器网络因其高度集成化和节约电源等优点,比采用传统的集中式数据采集方法更加高效实用.

英文摘要：

This paper presents the vibration test of a simply supported plywood plate using ISM400 wireless smart sensor developed by the Illinois Structural Health Monitoring Project（ISHMP）.Decentralized data aggregation（DDA）as well as centralized data collection（CDC）was used for data acquisition and processing.Then a time domain algorithms integrating natural excitation technique（NExT）and eigensystem realization algorithm（ERA）,was applied to identify modal parameters of the plate and the identification result was compared with the finite element result.The modal parameters（i.e.natural frequency and mode shape）identified from experimental data using DDA is not only in accordance with that using CDC,but also in accordance with the numerical simulation result,which shows that the wireless smart sensor networks（WSSN）based on DDA is reasonable and effective.Compared with conventional centralized processing technique,the unique features offered by distributed WSSN,including high integration and electrical energy saving,make deployment of a dense array of sensors on large civil structures both feasible and economical.